U.S. Healthcare Transformation: Glimpses of Reform

U.S. healthcare transformation has been the subject of innumerable conferences, debates and programs for many years, and social business will play a large role. Reducing cost without sacrificing quality of care has become the common goal, so I believe social business will be a key lever because social technologies dramatically reduce the cost of collaboration.

I have monitored healthcare reform for many years, and I sense that various factions, players and special interests are finally realizing that they must change. “Obamacare,” the protracted poor economy and a rapidly aging population are forcing many players out of their comfort zones.

I attended two events last week that provided interesting glimpses from behind the curtain, so I’ll share my notes here. One conference was co-sponsored by Baker & McKenzie and Deloitte, and the other was held at the University of Chicago Booth School of Business.

Technological Transformation of the Life Sciences Landscape (Baker & McKenzie and Deloitte)

Keynote—Harry Greenspun, MD (Deloitte, New York)

Harry outlined broad trends for healthcare and life sciences transformation.

• Overall healthcare trend: the provider focus is shifting from volume to value (cost/outcome); how to measure it though?
• Need to coordinate care, share information, engage patients, use analytics to measure outcomes.
• Sharing information has never been incented in healthcare; it requires mental changes as well as technology support.
• Doctors don’t know whether they’re good or not; very little reliable information available on outcomes; New York state has a database of cardiology outcomes; it’s a rare example.
• Coordinate care; there’s no “project management” in healthcare, where patients often wander among different providers and specialists; “islands of care.”
• Big disconnect: physicians want “quality of care” information, but patients can’t provide it; patients are focused on “service experience” because they have no healthcare/medical training to assess physicians/quality of care.
• Make healthcare more social to improve patient compliance; it’s a way to reward them for compliance.
• Physicians, when appropriate, can add value by connecting patients with each other; social tools will help with patients and their families, too, to coordinate care.
• Another disconnect: patients like care, which is expensive; they report lower satisfaction rates when providers improve utilization by cutting back to save costs.
• Information/big data/analytics can change behavior, but healthcare managers don’t trust it; for example, credit scores can help predict hospital readmission rates.
• Also, big data scientists don’t like healthcare data because it’s so dirty, imperfect; healthcare is replete with “islands of automation” whose data don’t mix well.

Panel One: Privacy—Jane E. Hobson (Moderator, Baker & McKenzie, London); Harry Greenspun, MD (Deloitte, New York); Brian Hengesbaugh (Baker & McKenzie, Chicago); Dr. Thilo Raepple (Baker & McKenzie, Frankfurt)

The first panel addressed “privacy,” which is poignant in healthcare—and a huge inhibitor in sharing information to enable better care.

• Privacy a key inhibitor to sharing healthcare data, and the regulations on its use are multiplying fast, which prevents sharing.
• Worse, there’s a broad definition of “personal data” (which means very little is available to share).
• Physicians don’t like to get personal data from patients (i.e. from social media) because they are afraid it will increase their liability (for example, if they use patients’ Facebook updates they might be required to monitor it, always.
• Telecoms destroy location data for the same reason; they want to escape liability.
• Social media is exploding data on how patients use and experience medication; and regulators and government take it seriously.
• Pharma is mashing up data via analytics to craft value propositions and pitch drugs, so business is innovating (because there’s less restriction on data use for business than for care).
• In Europe, data use is very restricted; when the data is received, the purpose is specified, and companies cannot reuse it for anything else, even if they deidentify it.
• Employers are collecting healthcare data in order to reduce costs.
• In Illinois, the legislature ruled that employers cannot force employees (or prospects) to turn over their social media credentials (enabling employers to snoop).
• To use data effectively, it needs to be tracked reliably (to insure various data points belong to a person or process, required to draw inferences from it); that’s where privacy’s a problem; even deidentifying data isn’t foolproof because it can be reidentified in many cases.
• Survey: the lowest trust among patients were payors, pharmaceutical firms and employers; highest trust were providers, hospitals and government; therefore, high-trust and low-trust players are collaborating to use data to improve healthcare value.
• Mobile apps, if they are designed for medical purposes, are strongly regulated in terms of data; however, general apps that can be used for medical purposes are not; it’s a big gray area.

Panel 2:

The Extended Healthcare Enterprise—Jane E. Hobson (Moderator, Baker & McKenzie, London); Yogesh Bahl (Deloitte, Chicago); Sam Kramer (Baker & McKenzie, Chicago)

• Global sourcing creates global extended enterprises, yet privacy and compliance make things very difficult for extended life science firms.
• Part of the problem is, it’s not obvious how to define when partners are “part” of an enterprise. For example, an overseas supplier makes a faulty part and a medical device fails, who is liable?
• Cross-border is the most difficult because laws are different in various countries (medical devices often have parts from suppliers in various countries, and they sell to clients in countries with diverse liability laws).
• CRO is big example.
• Data also presents problems; pharma and providers want to improve outcomes, i.e. monitor social media for adverse events.
• In general, outsource functions/processes to partners who have their compliance houses in order; for example, CRO/medical trials require strict security.
• Pharma and medical device mergers & acquisitions are starting to consider compliance, pre-deal; traditionally, due diligence only looked at financial measures, but they have learned that acquirees might have significant compliance exposure.
• 70% of clinical trials are a complete waste (recent research).
• Shared services can add value, but be careful with respect to compliance; IT outsourcing can be a good value for life science firms, but vendors need to be first class; procedures like the “clean desk policy,” which requires the provider to put away all information it was using for one client before s/he starts on another client, to avoid commingling data, are critical.
• When conducting due diligence for a deal, check things like the acquiree’s relationship with its local government, federal regulations in its country(ies) and culture.
• Data security and privacy are not atomized, i.e. via DRM-like devices; control is still at the network access and encryption levels; therefore, each country and region has different rules, adding complexity and cost.

Trends in Healthcare Consulting (University of Chicago Booth School of Business)

Principals at four consultancies discussed their healthcare consulting businesses, client situations and opportunities in healthcare consulting. All serve provider clients (hospitals and medical groups) as well as payors (healthcare insurance firms).

Panel Discussion—Michael Valitchka (Point B, Moderator); Larry Briski (Invoyent, panelist); George Mansour (PricewaterhouseCoopers, panelist); Nick Valentino (Navigant Consulting, panelist)

• The ACA (affectionately known as “Obamacare”) has generated a lot of consulting business, and there’s no end in sight; various players want help predicting premium and cost adjustments.
• Consultancies have many needs, and you don’t need healthcare experience to enter the field.
• Healthcare payor and provider clients at PwC want to know how to optimize their operations to take into account the new U.S. (state) insurance exchange markets.
• The ACA and the economy are raising healthcare costs; Boomers are a large demographic with high healthcare needs.
• The pressure to cut healthcare costs is intense and getting worse; it’s protracted, and for the first time.
• Many patients have not had healthcare for a long time due to lack of coverage and high costs; the ACA is bringing them back into the system; many haven’t had annual checkups in years.
• The ACA affects payors and providers somewhat differently; providers need to see patients to maintain their reimbursement rates, which is inefficient, it increases volume and demand on the system while supply of providers is constant.
• Exchanges inject dynamism into the system and increase the demand on the system, in theory, but how many people will pay the minor penalty instead of buying the “mandatory” insurance? No one knows.
• Providers will depend on nurse practitioners and physician assistants to take up the slack; providers need to increase the supply of care.
• Also the ACA models are based on younger, healthy people buying in, but many may pay the penalty and avoid insurance; payors need to know how to price their policies, so consultants are very busy.
• Trends during the next 5-10 years: consolidation, horizontally and vertically, among payors and providers; payors buying providers; hospitals buying faculties at Northwestern Memorial Hospital; HCSC bought the Montana Blues plan.
• Drugstores are opening “minute clinics” manned by nurses, with physician availability by phone.
• Medicare and Medicaid have quality of care discussions, and are starting to base reimbursement on outcomes; they are starting to introduce standards of care, outcomes, for hospitals and clinics.
• There aren’t yet quality standards that can help patients select coverage and select providers; we need data on physician success rates.
• Exchanges are then focused on access of insurance and providers, not quality, because no data is available; that’s coming.
• Patients are selecting physicians based on their Yelp reviews, but of course these are all based on “service experience” because other patients can’t evaluate quality of care (in terms of outcomes); how to measure outcomes reliably?
• Cost is key; 3/10 patients need care but don’t seek it, which increases cost when they go to emergency later; that’s 50 million people in the U.S.
• We need to focus on prevention (but it’s not reimbursed).
• ACNs are supposed to address cost containment and introduce feedback loops.
• Consolidation may help; Kaiser Permanente has had some good outcomes in California, quality of care has increased due to better coordination among Kaiser providers.
• Risk is a foreign concept to providers who are being forced to assume some of the risk (reimbursed for packages of care rather than each line item, i.e. test/operation); we all remember the HMO failure; ACOs will be similar if we aren’t careful.
• ACOs work better in dense population environments (cities); large payors are moving to ACOs, they think it’s better to be a part of it and to try to influence how ACOs develop; they want to know how to do risk transfer.
• Payors are risk focused, providers aren’t, but they will have to learn; follow up with patients; physicians usually don’t because they aren’t incented to; now they are because penalties for readmissions; providers are traditionally focused on volume,
• Payors will follow up with patients to make sure they are following doctor’s orders; they want to make sure the patient gets better by improving compliance, so they are moving to manage medical conditions.
• Technology investments can help; payors are getting more information on care by following up with patients; interoperability of software and hardware is low.
• Exchanges will not help in managing risk; their main thing is access now.
• Pay for procedure has always been the norm, so providers need to learn how to optimize; providers never followed patients across the “care stream”; only their piece of it, so no one has data to inform optimal care.
• Data analytics can help, but hospitals need to learn how to use it.
• Hospitals are buying small businesses (practices); providers and payors are collaborating and sharing data to develop optimal care protocols for specific populations; payors have data on outcomes for large patient populations.
• Payors are scared of being squeezed out as hospital groups in urban areas get bigger; at a certain point it makes sense for them to process their own insurance.
• Employers have it easier; some don’t hire smokers or force them to pay higher premiums; payors look at patients as customers, not employers, as patients pick their own coverage, but they don’t know how to relate to patients; they’ve never had to before; “customer experience” is an unknown concept.
• How to incent patients to make good choices? Consultants are doing a lot of surveys and testing concepts, trying to learn what works.
• Price matters, and patients still don’t pay enough for healthcare to influence their choices better; they need to be accountable; there’s so much waste; we need to reintroduce incentives.
• The system needs diverse skills, business, technology.
• Education costs and torts are hurting the system; physicians need to make a lot to pay off their education; malpractice is very high.
• Payors are introducing models in which patients promise not to sue for lower premiums.
• All kinds of transparency are happening with mobile devices, which help patients discover pricing discrepancies, manage records and appointments, etc. Examples are Zocdoc, Patients Like Me, Facebook integration.
• Physician rating systems are affecting choice, but for experience, not quality.
• Technology enables families to collaborate to help care for members with chronic disease.
• Need to get physicians involved with data so they don’t only rely on their own experience, which is small but on outcomes for thousands or millions of patients.
• Payors and providers are starting to collaborate to determine optimal care protocols; lab expenses, consensus on leading practices.
• Payors are scared of ACOs in cities.
• Of course the government is the biggest payor (Medicare); its data will be very valuable, can change the game.
• Providers will get the upper hand eventually.

Conclusions

• It was obvious from speakers’ remarks at both events that all players in the U.S. healthcare value chain are afraid of being disrupted; no one knows how the status quo will change.
• It is debatable whether healthcare is a “business” or a public service; in the U.S., it is treated more like the former, but that is being questioned now.
• Social business can enable all parties to collaborate much more closely, so that they can coordinate care better; this can dramatically lower costs. A very small portion of the U.S. population accounts for a large share of the total healthcare costs, so cost is very concentrated. Patients at end of life and with multiple chronic conditions.
• As elsewhere, “empowerment” is adding dynamism to the system; patients are discussing their health and care with each other, thereby educating each other and formulating preferences; similarly, providers are interacting with them online.
• I have written several healthcare social business case studies; also see the Social Business Opportunity in Healthcare microsite.
• KPMG analysis of the U.S. healthcare value chain; how various players are affected by the ACA.
• McKinsey paper on using big data in healthcare.
• Access more healthcare reform papers and notable posts.