Taking Patient Preferences Into Account When It Comes to Pursuing and Measuring Quality

Here's a thought: ask them what they want

One of the intellectual underpinnings of population health management is that the biopsychosocial dimensions of care is a huge determinant of real-world outcomes. As any doctor who takes care of flesh-and-blood patients knows, national treatment guidelines like these typically fall short of taking the human dimension into account. While there are plenty of good and bad reasons why docs are failing to take advantage of guidelines, one is their sterile one-size-fits-all approach that often fails to account for physician awareness of their patients' risk tolerances and economic circumstances. What's more, many widely promoted treatments only offer a small absolute benefit.

Fortunately, this disconnect is bubbling up into the mainstream scientific literature. The latest example is this Viewpoint that appears in the October 28 issue of JAMA. The authors point out that the perspectives of expert physicians who develop guidelines are typically different than the general public, caregivers or persons with a disease. For example, while the NCQA promotes an A1c threshold as a important measure of diabetes care quality, a compelling survey of patients with diabetes suggests that that emphasis may be displaced.

Where to from here? The JAMA authors offer three commonsense recommendations. Future guidelines should:

1. be developed with the input of patients and frontline clinicians.

2. encompass the full range of patient experiences, not outcomes. This means accounting for the  burden, impact on quality of life and role function dimensions of any treatment recommendations.

3. avoid strong recommendations when the best course of action depends on the patients' context, goals, values and preferences.. Lacking a clearly advantageous outcome with minimal side effects, guidelines should offer a conditional suggestions.

The DMCB modestly offers up three additional suggestions for the population health community and other stakeholders:

1) Absent a satisfactory guideline process from the usual national organizations, it would not be a bad idea to take this bull by the horns and develop a parallel set of guidelines that meet the principles outlined in this JAMA article.

2) Organizations like the NCQA and NQF need to be more flexible in promoting evidence-based guideline-based metrics by moving away from a reliance on their monodimensional clinical measures and toward more nuanced measures of meeting patient preferences.

3) Finally, while national variation in health care delivery is a huge challenge as we continue to build a coherent health system, it may be time to reconsider the notion that all variation is bad. Human beings are variation, and the likelihood of imposing local "best practices" across the U.S. will not be in the best interest of patients with different views of what it best for them.

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Quality Improvement Ver. 2.0?

Throughout its medical career, it's safe to say that the Population Health Blog has been quality-improvement ("QI") averse. While the PHB "got" the need for measurable outcomes, the jargon ("barrier analysis"), expertise (careerism) and culture (heavy on "administration") made it treat QI like an EHR alert: something to be tolerated, not embraced.   

After reading this on-line AHRQ manuscript on primary care QI, however, the PHB is reconsidering the topic.

Naturally, for all the wrong reasons.
 
The PHB explains.

According to the brief:

1) QI can be defined as continuously assessing performance over time to make ongoing adjustments in care processes  Like it or not, QI is being increasingly linked to licensing, accreditation, public reporting, media scrutiny, payor involvement and growing patient consumerism. It's true for hospitals, and it's just a matter of time until that extends to the outpatient arena.

2) Unfortunately, QI needs the three things that are in short supply in most outpatient settings: staffing, resources and commitment. Two other challenges include the never-ending work of patient care and the lack of any direct or indirect financial benefit. 

3) As a result, if primary care practices are going to meaningfully "do" QI, they'll need external support.  That means personnel/consultants who can train, provide technical assistance, find resources or suggest best practices. Large health systems may be able to adapt this from their hospital QI programs.  Smaller or independent clinics may have to turn to the overlapping regional alphabet soup of AHECs, RECs, QIOs, PBRNs, payer, employer and professional initiatives paid for by the Feds, states, insurers and foundations.  The chances of success will be greater if there are financial incentives (such as a piece of any shared savings) and networked learning involving other like-minded clinics.

The PHB's knows the AHRQ authors mean well, but wonders if it isn't time to start thinking about QI Ver. 2.0.  It would involve some of the following elements:

Turn key: easy to import with absolute minimum fuss, time to implementation, workflow disruptions and reliance on human guidance.

A contracted entity can remotely tap computerized billing, insurance claims or electronic record systems in a matter of days, letting the docs continue to focus on patient care.  If patient surveys are necessary, use text messaging or interactive voice response.

High tech: Cloud-based data collection, storage and reporting.  All the better if it's automated and scalable.

Once the data are collected, computers can calculate trends, means, standard deviations and statistical significance.  The process can be standardized and auditable.

Decision support: Link any insights to the artificial intelligence that guides patient care.

As point-of-care guidance on diagnosis or therapy grows more sophisticated, it can use the clinic's QI data to change processes and improve outcomes.

By the way, the PHB suggests one entity that is best able to champion this are the population-health care management programs.  They understand the need, possess much of the technology and could use QI to further their value proposition.

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AHRQ Says the Patient Centered Medical Home (PCMH) Does Not Lower Health Care Costs. Here's 5 Reasons To Not Believe Them

While you read the following, keep in mind:

1. Using traditional research to detect a "statistically significant" decrease in insurance claims expense is notoriously difficult.

2. There's scientific statistical proof and then there is a reasonable business assurance.  The latter may be enough for business-minded health insurers.

3. The conclusion is based on published research.  Unpublished "in house" data have convinced many insurers to include the medical home in their covered benefit.  They know something AHRQ doesn't.

4. While medical homes alone may be insufficient to save money, that doesn't mean that medical homes that are part of a package of interventions (value-based purchasing, P4P, vendor-based population health management or an ACO) are unnecessary.

5. While there is no evidence of savings, there is also no consistent evidence of increased cost. That means the quality associated with the medical home represents high value.

That being said, the U.S. Agency for Healthcare Research and Quality (AHRQ) Evidence Report Technology Assessment on the Patient Centered Medical Home says:

"Based on a combination of good- and fair-quality studies, there is a low strength of evidence that PCMH implementation may lead to lower utilization (inpatient and emergency department) for some subgroups of patients, but this effect was not uniform. Moreover, total costs were not lowered in the reviewed studies.

However, three observational studies specifically designed to test PCMH do report lower inpatient and emergency department utilization among patients in the PCMH program. However, total costs were not statistically different for PCMH and non-PCMH patients in the three studies. None of the clinical trials of functional PCMH interventions had statistically significant differences between intervention and control arms for inpatient or emergency department utilization.

No studies reported statistically significant cost savings among PCMH patients. In fact, when taking into account program costs, two studies, one good-quality trial and one fair-quality observational study, reported greater total costs among intervention patients."

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