Where Are We Now?
In the current study, Tisano and colleagues  investigated the relationship between patient factors (both modifiable and non-modifiable) and patient satisfaction in an outpatient clinic. They chose to specifically explore how certain demographic variables (age, race, gender, insurance status) and certain patient clinical factors (BMI, depression status, Charlson comorbidity index scores) were associated with the likelihood that a patient would be satisfied with his or her care. A main research question focused on the association of depression with satisfaction, something that has been studied extensively in orthopaedic surgery [3, 14]. Not surprisingly, they found a relationship between patients who had a diagnosis of depression and their reporting of lower satisfaction with their medical care.
Orthopaedic surgeons do not consistently screen for or document signs of depression, likely because of provider and patient discomfort in discussing depression, non-standard methods for diagnosing depression, and cultural and other social factors affecting how people perceive depression [5, 15]. Depression also has all of the attendant issues of documentation and coding of complex comorbidity profiles in patient care .
The difficulties of measuring patient satisfaction in orthopaedic surgery, especially in examining the relationships between patient satisfaction and clinical outcomes, have been discussed in prior editorial in this journal .
Where Do We Need to Go?
While patient satisfaction is a measure that is becoming more important in hospital and physician ratings and in payment for services, there is little consensus regarding whether satisfaction is definitively correlated with technical quality of care or patient-reported outcomes following surgery . This, in addition with concerns about methodological issues related to sampling and response rates of surveys , makes it difficult to determine what should and could be undertaken to improve patient satisfaction, although studies have suggested that better provider-patient communication and shared decision-making, along with the application of patient satisfaction results to focus on improving care processes rather trying to apply them to outcomes, could be promising .
We are now practicing in an era where payment programs and their related incentives do, and perhaps even should, affect how we provide care. What is best for the patient is not as straight-forward in times when value-based purchasing and patient consumerism are everyday concerns.
Put in this context, how do we improve patient satisfaction? Current research has shown that there are certain factors, such as patient perception of pain control, not-for-profit status of the hospital, and demographic factors, that seem to correlate highly with patient satisfaction, but study methodologies and available data often have methodological problems, including sampling frames, differing focus of questions, and varied response rates . As providers, we need to embrace the challenge of looking beyond data that are easily available from hospital and clinic-based satisfaction surveys to design better methods and practices that could positively impact patients.
Another challenge is determining how to ensure that patients with depression are effectively captured from administrative datasets. Reporting of depression in medical records and administrative databases is increasing , most likely due to increasing acceptability of screening and treatment for this condition. However, the diagnosis of depression using administrative coding often does not provide enough information for us to stratify the needs of patients with mild, moderate, or severe depression, nor does it separate these groups from other mental conditions such as generalized anxiety disorder, panic disorder, or lack of emotional support . There are ICD10 codes that could help give much more specific information about emotional conditions, but those codes do not affect reimbursement, and therefore, are not always prioritized during the coding process. Because of small sample sizes, research studies tend to link all diagnoses corresponding to depression into one category, further diminishing our ability to truly examine relationships between patient factors and patient outcomes.
Although Tisano and colleagues  found a relationship between patients who had a diagnosis of depression and their reporting of lower satisfaction with their medical care, there are several questions that future studies should consider exploring. For example, is depression a transient condition due to our patient’s present condition, or is it something more permanent? Should screening for depression and related conditions be a required part of treatment of orthopaedic conditions, particularly prior to surgery? Should a diagnosis of depression preclude patients from receiving treatment?
How Do We Get There?
The discrepancies between perception of care, reality of care, and what can be abstracted and reported, whether in administrative databases or through surveys, will not be easily overcome . While using large, national databases as opposed to smaller, single-institution datasets can give us a broader perspective in determining relationships between patient factors and outcomes, there are obvious drawbacks to using administrative data compared to data from medical charts. New data-science approaches, such as using machine learning and other data mining techniques could help us analyze the nearly infinite amount of information that resides in medical records, and that information could be used to develop more-accurate predictive models for determining what factors really influence technical outcomes such as function, pain, and stability and patient satisfaction after treatment.
Another approach to measure both technical outcomes and patient satisfaction would be to systematically use other tools to supplement standard instruments such as the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS). Research has shown that using patient-reported measures like Patient-Reported Outcomes Measurement Information System measures can yield a more well-rounded understanding of patient conditions [2, 7] and how they relate to patient satisfaction. Adding additional surveys using different, yet complementary methodologies, could also add important information, especially to assess concerns from the large proportion of patients who are not selected to receive HCAHPS surveys or who don’t return them .
Expanding the use of diagnostic tools and patient-reported outcomes would be helpful for investigating and confirming the constellation of symptoms that could make up a diagnosis of depression or other mental disorders, improving accuracy and sensitivity both from a medical record perspective and for subsequent administrative databases . Having better information about depression can lead to better screening and treatment for this condition for patients having orthopaedic surgery and better prepare these patients for what to expect post-operatively . Longer-term studies on the impact of depression (and other comorbidities) on patient outcomes and satisfaction following orthopaedic treatment would certainly go a long way in designing more-comprehensive and multi-disciplinary interventions to improve outcomes in general.
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