University of Wisconsin–Madison Medical College of Wisconsin

Small Is Beautiful* – or Is It?

John J. Frey III, MD, WMJ Medical Editor

WMJ. 2018;117(3):102-103.

Download full text pdf.

One of the more interesting areas of discussion in health care in the United States is, on one hand, the value of “big data” in improving care and, on the other, the value of downsizing practices away from large systems and creating small practices with a fixed population of patients. Wisconsin and the Upper Midwest may be an important laboratory for examining those two seemingly disparate trends, and this issue of the WMJ contains articles that illustrate both.

Perhaps no region of the country has been as dedicated to the creation of larger and larger health systems with emphasis on multispecialty group practices as Wisconsin and Minnesota. Madison and Konrad, in their seminal paper on the history of employed physicians and large groups wrote 30 years ago, “The revolutionary change, the one likely to introduce a new era of medical practice, is the ascendancy of the organization-employed physician.”¹ Well that era is here and has been for quite a while. Nationally, physicians are employed in systems rather than owning their own practice either solely or in partnership. Family physicians nationally are 71% employed, with 21% being members of large multispecialty groups and 28% employed by hospital health systems. (Facts about Family Practice. American Academy of Family Physicians.) Wisconsin has led the country in the percentage of employed physicians where estimates are that 50% of all physicians in the state are employed in one of 17 large group practices.

So the review by Carlesare² and the Office of Professional Satisfaction and Practice Sustainability of the American Medical Association on the rise of direct primary care practices might seem like the description of a small sailboat in a sea of ocean liners. However, the forces that Madison and Konrad wrote about in the 1970s that were driving physicians to form groups, Carlesare argues, have come back to push medical practice to exploring older ways of organizing practice: small or solo groups, direct “retainer-based” business models, low overhead, high continuity, and neighborhood based. Many physicians are choosing a higher risk, likely lower paid practice model over comfort, salaries, and routine. Not only do they feel that they have more control over their lives, they feel a sense of ownership. Anyone who has gone to a locally owned restaurant or small business or talks with a dairy farmer understands the motivation behind physicians wanting to have a sense of ownership. An abiding belief in themselves motivates people all over the world to make a business theirs.

A national study by Eskew and Klink about the distribution of direct primary care practices in the United States found that Wisconsin was among the 3 states with the highest number of registered direct primary care practices.³ That doesn’t mean there are a lot, but most primary care physicians know of someone in their community who has or is thinking about transitioning from a large group to a direct primary care practice. So far, the movement is under the radar, but not likely to remain there as long as the dysphoria among employed physicians remains high. Carlesare’s article in this issue will add to the discussion of what has increasingly become an alternative to the large multispecialty and hospital owned groups in this country. One challenge that might change the current malaise in large multispecialty groups might be for them to use the experience of direct primary care practices to create small, neighborhood, high value, low overhead practices within large systems. There is really no reason except inertia for large groups in Wisconsin not to try that approach. Maybe David has something to teach Goliath.

Big Data for Better or Worse

Anyone practicing medicine in the past 25 years has felt the increasing burden of measuring things. Where it all started is hard to pin down, but measuring things came with good intentions driven by the simple logic that if we don’t understand where we were, we will not be able to know where we should go. Measuring was simple because the tools we had were simple—cards, ledgers, typed lists, and one’s own memory. It took Hart a decade to publish the first measurement of the blood pressure of everyone in a community in 1970.⁴ The publication of studies that showed wide variability in quality and cost drove government, the public, and eventually insurers to decide that decreasing variability and increasing reliability was an important goal. The march to quality had begun, along with the continuing disagreement about what constitutes quality. The result was, in effect, if we can’t agree on quality, we will measure everything in the hope of finding it.

Decades later, the advent of supercomputers and electronic health records expanded ways to collect data that required codification, analysis, and use. An entire industry for coding, measuring, reporting, and forcing compliance with “standards” was launched. The Coding and Compliance industry has arguably become the largest overhead cost in American medicine in the past 25 years. Health systems and insurance companies have entire buildings full of people whose job it is to measure, analyze, and provide “oversight” for clinicians. Has it made a difference? Not particularly.

The Commentary in this issue from Stiles, Barrett, and Beasley⁵ is an attempt to bring some sense to the runaway world of measuring everything. They review the history, intentions,results, and consequences of using metrics for every aspect of medicine and make a case for bringing measurements back to their original intent – constructive data to help physicians understand how to improve our care without oppressing our lives. They don’t advocate moving away from measuring or collecting information but want to revise the process to center on physician and patient and community needs, not insurance or corporate needs.

On the other hand, Munson and colleagues demonstrate the value of big data and accurate measurement to affect important clinical outcomes.⁶ They describe a statewide, systematic collection of evidence for resistance in pathogenic bacteria and, not surprisingly, find that there are wide variations in regions and communities. Treating common infections may require different antibiotics in Rhinelander, Wisconsin compared to Kenosha. Standardization of data is essential to forming clinical care initiatives. Just as all politics is local, much of therapeutics is local. One of the largest obstacles to the rational use of antibiotics remains the dissemination of information and education about its use to the practicing community. Electronic Health Records may be useful in this regard but require individualization and continuous updating from studies like Munson et al.

Clinical Studies and Clinical Stories

The brief research report from Rongstad and colleagues about food insecurity in a convenience sample of pediatric patients in Dane County makes the case for using screening tools for social determinants of health.⁷ However, the small percentage of patients who have food security issues in their sample compared to statewide studies or studies from other regions showed different results. A study of children visiting an emergency department in Milwaukee found much higher levels of food insecurity.⁸ Not only where you live but where you access care might be worth analyzing.

The study by Berg and colleagues shows an essential fact of prevention and clinical practice: if we ask about risks, we need to have an action step based on the answer that has a chance of mitigating that risk.⁹ In this case, they studied whether primary care clinicians ask patients about smoking (they do for the most part but still ask less often young people and people of color) and whether, having identified smokers, clinicians would invite them to engage in an effective intervention to decrease or stop smoking (they did two-thirds of the time). Having something to offer other than encouragement is an important incentive for clinicians. This study shows that, armed with help and an intervention that has a good chance of working, primary care clinicians will take a more active role in preventive counselling.

Two case reports to point out that rare things happen. Muganda and colleagues describe a case of meningoencephalitis in a toddler due to raccoon roundworm.10 Fortunately they were able to treat the child who continues to have some residual neurological problems. How did he get it? Ask parents if a child exhibits pica or geophagia, and while some research supports the value of dirt for the enterobiome, dirt from the wrong places can be fatal!

Libricz and colleagues report on 2 cases of inadvertent cannulation of the carotid artery when trying to place a central venous line.11 The cases demonstrated quick thinking and recovery of the cannula using a technique assisted with ultrasound. One hopes this never happens but if it does, it is nice that there are some alternatives possible.

Finally, a remarkable “As I See It” essay/story from Ahearn is a moving account of the terribledisruption that mental illness can bring to end-of-life care.12 Her essay raises the specter of who and what to believe as a palliative care clinician and how the line between truth and delusion can be a very fine one at times.

 References
  1. Madison DL, Konrad TR. Large medical group-practice organizations and employed physicians: a relationship in transition. Milbank Q. 1988;66(2):240-282.
  2. Carlasare LE. Defining the place of direct primary care in a value-based care system. WMJ. 2018;117(3):106-110.
  3. Eskew PM, Klink K. Direct Primary Care: practice distribution and cost across the nation. J Am Board Fam Med. 2015;28(6):793-801.
  4. Hart JT. Semicontinuous screening of a whole community for hypertension. Lancet. 1970;2(7666):223-226.
  5. Stiles MM, Barret B, Beasley JW. METRICS for metrics. WMJ. 2018;117(3):104-105.
  6. Munson E, Hueppchen E, Zeman H. Surveillance of Wisconsin organisms for trends in antimicrobrial resistance and epidemiology: introduction to the program and summary of 2016 geographic variation. WMJ. 2018;117(3):116-121.
  7. Rongstad R, Neuman M, Pillai P, Birstler J, Hanrahan L. Screening pediatric patients for food insecurity: a retrospective cross-sectional study of comorbidities and demographic characteristics. WMJ. 2018;117(3):122-125.
  8. Pabalan L, Dunn R, Gregori K, et al. Assessment of food insecurity in Children’s Hospital of Wisconsin’s emergency department. WMJ. 2015;114(4):148-151.
  9. Berg KM, Smith SS, Piper ME, Fiore MC, Jorenby DE. Identifying differences in rates of invitation to participate in tobacco treatment in primary care. WMJ. 2018;117(3):111-115.
  10. Muganda GN, Akagi NE, Fagbemi OD, Chusid MJ, Nelson A. Rapid therapeutic response to eosinophilic meningoencephalitis in a toddler with Baylisascaris procyonis infection. WMJ. 2018;117(3):130-132.
  11. Libricz S, Sen A, Davila V, Mueller J, Chapital A, Money S. Ultrasound-enabled noninvasive management of inadvertent carotid cannulation. WMJ. 2018;117(3):126-129.
  12. Ahearn E. The loneliness of mental illness at the end of life. WMJ. 2018;117(3):101.
Share WMJ