Ideal Medical Practices

Hospitals, Practice Administrators and Clinicians: You Gotta Learn to Love Patient Ratings – Health Affairs Blog

You are increasingly being held accountable for the outcomes of the health care you deliver. Pay for performance; shared savings in ACOs; public report cards…the list of strategies to monitor and measure the effects of your efforts is lengthening. Many of you seem dismayed by the increased weight accorded to the patient experience of care ratings embedded in most of these programs.  Here’s why you should embrace them: The care you deliver cannot improve our health outcomes or even maintain passable ones without the knowledgeable, active participation of us patients and our families.

via healthaffairs.org

There is good evidence linking patients' experience of care to important outcomes.  Here are a couple of examples: 

• Hospitalized Medicare beneficiaries who can't tell who is running the show and perceive conflicting messages from clinicians are much more likely to be readmitted within 30 days than those reporting good experiences. (Boulding 2011)
• People receiving care in practices with good access, less wasted time, and better communication are more likely to report that treatments have helped reduce problems with pain & emotions, have improved markers of chronic conditions, and reduced use of the hospital & emergency room. (Wasson 2006)

We think that if we adhere to evidence-based guidelines our patients will achieve excellent outcomes, but if we also know that if patients experience delays getting a timely appointment they are less likely to follow up for needed care (Lacy 2004), and people who experience in-office waits and delays are less likely to follow through on appropriate care recommendations (Ling 2006).

Clinician adherence to evidence-based guidelines only goes so far and all the best health information technology for disease tracking is of limited use if the health care team fails to communicate effectively with people who struggle to manage their conditions.  Before we write people off as "non-compliant" we can and should ask ourselves if we have inadvertantly created a series of hurdles and barriers that negatively impacts our patients.

These fundamental attributes of primary care are a good starting point:

1. Access:  how easy is it for people to get a timely appointment?  The ultimate answer comes from those you serve - don't just rely on administrative data.
2. Person-focused care over time:  what percent of your patients say that they can identify a 'go-to' medical person?
3. Comprehensiveness: Recognizing that people must manage their own conditions the overwhelming majority of time, what percent of those with chronic conditions report that they understand what to do and have the confidence to manage?

We showed that it is possible to implement tools to measure and address these issues even in solo independent primary care practices. (Moore 2007)

I agree with Jessie Gruman that we should embrace patient experience data as a powerful addition to our understanding of system performance as well as insight into why some people struggle with effective self-managment.

L Gordon Moore

 

Boulding W, Glickman S, Manary M, Schulman K, Staelin R.  Relationship between patient satisfaction with inpatient care and hospital readmission within 30 days  Am J Manag Care 2011 17(1): 41-48

Lacy, N., Pullman, A. Reuter, M., Lovejoy, B. Why we don’t come: Patient perceptions on No-shows. Annals of Family Medicine 2004;2:541-545.

Ling BS, Klein WM, Dang Q.  Relationship of communication and information measures to colorectal cancer screening utilization: results from HINTS.  Journal of Health Communication. 11 Suppl 1:181-90, 2006.

Moore LG, Wasson JH.  The Ideal Medical Practice Model: Maximizing Efficiency, Quality, and the Doctor-Patient Relationship.  Family Practice Management September 2007 pp. 20-24.

Wasson, J. H., Johnson, D. J., Benjamin, R., Phillips, J., & MacKenzie, T. A. Patients report positive impacts of collaborative care. Journal of Ambulatory Care Management, July-September 2006 29(3), 199–206

Strong and weak indicators of quality and outcomes: not what you'd expect

The prevailing quality paradigm starts with the simple observation that we can observe gaps in care when we create an evidence based guideline and assess observed care against expected.  One study says that we meet these expectations about 56% of the time.[1]

This observation leads to the seemingly logical conclusion that we can aggregate gaps in care as strong indicator of quality.  This is important as we assume that more of this quality will lead to improved outcomes.  We know from other studies that quality and cost are out of whack in the U.S. and health care costs are sucking the life blood out of employers, further exacerbating dismal job growth.Because we desperately want improved quality, we must have more of this gap closing work.

The prevailing quality paradigm has a number of flaws.  It is expensive, overly focused on process measures, and may not predict the outcomes we want and need.

Expensive

Delivering evidence based care is a good thing, but the burden of managing the vast array of discrete data elements is beyond the capabilities of the vast majority of EMR vendors in spite of their claims to the contrary.  Data entry is laborious and back end analytics infuriatingly complex, weak, or non-existent. Vendors have jumped into the breach to extract information from electronic records and even dictations but these solutions add significant cost that might not be recuperated in outcomes.

Overly focused on process

With years and years of disease management experience we know that process improvement does not always result in outcomes improvement.  In a time of limited resource we should avoid the added cost and work burden of meaningless measurement.

Weakly predictive of outcomes

Making the case is a recent article from Duke.  Boulding and colleagues used Hospital Compare data to analyze thousands of hospitals, looking at predictors of re-admission.  They found evidence-based gap analysis a weak predictor of outcomes (re-admission in this case).  The strongest predictor was the patients report of good communication.[2]

This study adds to the growing literature that is trying to tell us something:  Patients perception and report of their care is tapping very important attributes of quality.  These attributes appear to have strong correlation with important outcomes.

Good patient experience data can inform hospitals about structural weakness in communication that increases readmission risk.  Patient report on primary care key performance indicators (access, person focused care over time, comprehensiveness, care coordination) can identify structural weakness far upstream.  When we address these structural elements we improve population health in meaningful ways.

This is a measurement burden we can bear. This information is a powerful addition to our understanding of quality and outcomes. The health care industry tends to disparage or only provide lip service to patient-reported outcome measures.  We continue to do so at our and our patients' peril.

 

[1] McGlynn, E. A., Asch, S. M., Adams, J., Keesey, J., Hicks, J., DeCristofaro, A., et al. The quality of health care delivered to adults in the United States.  N Eng J  Med, 2003; 348, 2635–2645.

[2] Boulding W, Glickman S, Manary M, Schulman K, Staelin R.  Relationship between patient satisfaction with inpatient care and hospital readmission within 30 days  Am J Manag Care 2011 17(1): 41-48

Managing population health: integrating behavioral health and primary care

I just read through an interesting policy brief from RWJF on integrating behavioral health and primary care:

Druss BG, Walker ER.  Mental Disorders and Medical Comorbidity  Research Synthesis Report No. 21 Robert Wood Johnson Foundation

Their review of the literature supports the shift from disease to person/population health management that I've described in the past.

• Many people with chronic conditions have co-morbid mental and behavioral health issues
• These individuals suffer worse outcomes and drive a disproportionate share of health expenditures
• The co-morbid conditions are more than additive in impact
  • The presence of either increases the probability of the other
  • Mental health disorders dramatically increase the probability of high-risk lifestyle issues (e.g. smoking, obesity, lack of exercise)
• “'Collaborative care' approaches that use a multidisciplinary team to screen and track mental conditions in primary care settings have been the most effective in treating these conditions"

More effective total population health can be achieved by:

• Screening all using a behaviorally sophisticated tool like HowsYourHealth
• Integrating behavioral health in primary care
  • Brief input on diagnosis and treatment plans
  • Brief intervention
  • Facilitated referral
  • Case management for individuals, not just conditions

Success requires moving from disease to population.  Early strategic choices by nascent ACOs could either tie up scarce resources in disease, running the risk of inadequate impact on total population outcomes.