“How do you feel?” It’s the simplest and arguably the most important question in all of medicine. Even with the burgeoning complexity of our health care knowledge and technology, it is still the most important question to ask, and the most important to answer. It would be the first item on any doctor’s checklist during an initial exam, the last question that should be asked before a discharge from the hospital and the first question asked during follow-up. Arguably, it’s all that really matters. How does the patient feel?
Unfortunately, it’s the question we’re not asking, at least not in any structured or consistent way. More precisely, we don’t routinely ask about how a patient fared following treatment.
Amidst all our knowledge, systems and funding for comparative effectiveness and medical research (approximately $100B in the U.S. each year), we don’t have much of a clue about the outcomes of actual patients treated in the real world. Phase-four trials of medications, the evaluation of patients’ functional and health status following surgical therapy, the comparative effectiveness of lifestyle changes and watchful waiting – these are all things that we physicians don’t generally collect, analyze or report upon, although there’s little doubt that we care.
We care if Helen, who underwent a radical mastectomy 10 years ago and brought the office staff cookies, beat breast cancer. We care if Charles had a good quality of life following prostatectomy, and we care if the new blood pressure medicine we started Gina on was more effective than the old therapy. We may seem like an “out of sight, out of mind” group, but we’re not. But how often do we ask? How often do we ask about the outcomes of patient care in a way that would allow us to better understand what works in health care, and what does not? We inherently trust the research that would guide a new drug or therapy to market, but beyond that, our knowledge of population-wide outcomes is “lost to follow-up.”
Whether its physicians or policy-makers, there is definitely support for collecting patient-provided information. Dr. Don Berwick, appointed by President Obama to be the next CMS administrator, wrote in his December, 2009 article in JAMA, “Measuring Physicians’ Quality and Performance, Adrift on Lake Wobegon:” “(P)atients can and should be asked directly about their experiences of care. The uniform use of the Hospital Consumer Assessment of Healthcare Providers and Systems survey measures in Medicare goes in the right direction, but much more should be invested in listening to patients and their families, helping them to describe how well they feel treated. The correlations between such ratings and pure, technical care quality are modest, at best, but attributes of care like “patient-centeredness,” “timeliness,” and overall responsiveness that patients can and do observe, are important qualities in their own right and each physician’s entire patient panel can contribute to sample size for these qualities.”
The citation that Dr. Berwick referenced on the modest correlations between patient ratings and technical care quality is entitled Quality monitoring of physicians: linking patients’ experiences of care to clinical quality and outcomes by TD Sequist. He and his colleagues studied patient experience survey measures including doctor-patient communication, clinical team interaction, health promotion support, integration of care, office staff, visit-based continuity of care and organizational access, and their correlation with quality measures (HEDIS prevention, disease monitoring and outcomes measures, which are all technical care quality metrics).
The challenge with using only technical care quality metrics is that in most smaller practices there is either a lack of structured data or an insufficient number of patients to achieve a sample size with any significance for most quality measures. Rather than limit outcomes measurement to large practices, there should be an opportunity to use the patient to provide feedback about what matters most to them: whether or not the treatment worked (or is working). There is a much greater likelihood in small practices that sample sizes using this method will be adequate.
Hospitals have a higher patient volume than medical practices, and so their job of submitting quality measures to CMS is a bit easier (and soon these “Core Measures” will be used as part of value-based purchasing). But even in hospitals how is it that we require the public disclosure of 12 acute MI care measures from every hospital in the U.S., and yet we don’t have any information whatsoever on how those patients fared a year or two after treatment? We don’t have that information available by hospital, and certainly not by physician. How is that we can ask physicians to submit seven PQRI measures surrounding diabetes care, but only the HbA1c measurement gives any real insight into the outcome of care (and even that requires coded lab result data)?
I’ve had the opportunity to read a couple of recently published books that examine the quality of our health care system and models for improvement. In Dr. Thomas Lee’s and Dr. James Morgan’s Chaos and Organization in Health Care, the authors argue that our growing knowledge and technical prowess have resulted in chaos, and the way forward out of this chaotic cloud is to create “systemness”, or organization. Whether through the use of electronic systems, better coordination of care, payment reform to encourage accountable care or through the public reporting of patient care – or some combination of these – organization needs to arise out of the chaos in order for patients, providers and payers alike to create a more effective and efficient health care system.
In his book, The Checklist Manifesto, Atul Gawande recognizes that there is great benefit in the knowledge and technology of modern health care, with the caveat that sometimes simple checklists are needed to ensure we have our bases covered to ensure patient safety and avoid unnecessary complications.
In both these “must read” books, it is recognized that our system is chaotic, and there are practical (and sometimes very simple) steps that can be taken to improve it. Both works reinforced for me the importance of the voice of the patient, and that “Ask the patient how they feel” should be listed on performance measurement checklists.
So how can we use patient-reported information to reliably measure outcomes? Whether for the purpose of determining the most effective treatments or for determining which physician or hospital is providing the best care, having patients self-report their outcomes will likely involve measuring their baseline health and functional status, including both physical and mental health, and their health and functional status at a specified period of time following treatment. It’s important to collect information about co-morbid conditions to adjust for the severity of the patient’s health, there needs to be reliable sampling (i.e. patients can’t be cherry picked), and there will need to be disease- or treatment-specific questions at baseline and in follow-up.
Here are a few examples:
- Knee surgery: In addition to baseline and post-therapy health and functional status assessment, it is important to understand how well controlled pain is, whether they were able to return to their work or favorite hobbies and whether or not their expectations of therapy were met.
- Prostate cancer therapy: In addition to functional and health status, it is important to understand if the patient experiences incontinence or impotence, their level of pain control and if their expectations of therapy were met.
- Diabetes care: Health status, blood sugar control and quality of life, along with whether their expectations of therapy were met, measured over time.
- Back surgery: In addition to functional and health status, it is important to understand pain control, if they are able to return to work or their hobbies, if they’re experiencing neurologic symptoms and (seeing a pattern here?) if their expectations of therapy were met
Notice the importance I place on whether the patient’s expectations of therapy were met. Fundamental to the results of asking patients about their outcomes is the expectation that was set before therapy. It’s ironic to think that patients who have much more severe illness may have better self-reported outcomes because their expectations might be more realistically set compared to more healthy patients (for whom a rosy picture is almost invariably painted).
Setting more realistic expectations will mean that the outcomes that patients report will likely be better (AND coincide with higher satisfaction). Perhaps that’s one of the reasons we don’t routinely ask patients “How do you feel?”. Maybe we’re worried that the expectations we had set were not met. But maybe, just maybe, if we partner with our patients and set more realistic expectations we can ask them “How do you feel?” without hesitation, routinely, and in a structured and consistent way… following the initiation of any therapy… and not only might we start gearing our therapies to those that result in the best patient-reported outcomes, we might even agree to be measured on the results.
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