Alongside the continual optimization of orthopaedic surgical procedures and treatment options, determination of factors associated with or predictive of successful surgical outcomes holds primacy. As a result, the impact of patient-level psychosocial influences on surgical outcomes for orthopaedic procedures is gaining momentum as a field of study. The effort has been empowered by the development of the Patient-Reported Outcomes Measurement Information System (PROMIS). PROMIS item banks allow computer adaptive tests (CAT), which greatly reduce the response burden for patients and make the routine collection of patient-reported outcomes, including depression, in clinics feasible. PROMIS measures are carefully constructed,1–6 both widely validated and found preferable to legacy and other measures,3,7–9 and easy to administer and interpret.
Being one of the two most important psychosocial correlates of disabling musculoskeletal pain,1 perioperative depression can negatively influence magnitude of disability,10 increase postoperative complications, decrease functional improvement, lengthen rehabilitation, prolong hospital stays, increase health resource utilization after discharge, and increase long-term dissatisfaction;11–19 misinterpretation of pain perceptions is the other, interrelated correlate.20,21 Given the range of associated deleterious outcomes, it follows that it is important for surgeons to identify symptoms of depression as a modifiable risk factor in their patients and be aware of the impact that depression can have on surgical outcomes.18 The routine collection of the PROMIS-Depression (D) scores helps to make this possible.
Patients with depression across a variety of orthopaedic surgeries have been shown to have increased odds of worse outcomes. For example, among patients who underwent total joint arthroplasty (TJA), patients with depression experienced improvement in their depressive symptoms after TJA and experienced functional gains equivalent to patients without depression, yet they were at increased risk for persistent pain, dissatisfaction, postoperative complications, incurring higher costs, and worse perioperative patient-recorded outcome measurements (PROMs).22 Further, preoperative PROMIS threshold scores, including for depression, can predict achievement of a minimum clinically important difference (MCID) postoperatively among patients undergoing total shoulder arthroplasty (TSA), total knee arthroplasty (TKA), and total hip arthroplasty (THA) and magnitude of improvement after foot and ankle surgery.12,23 Patient selection for orthopaedic surgeries of any nature is critical; and preoperative considerations regarding psychosocial factors, including intervening with patients who have depression and informing them about the potential for increased complications, is important since these factors impact physical recovery after surgery.24
However, physicians are reluctant to intervene, and physician education aimed at increasing rates of depression recognition and intervention has been found to be largely ineffective unless additional infrastructure and dedicated support staff are included.25–30 Still, clinical practice guidelines released in 2021 for health care providers treating adults with spinal cord injury recommend screening for depression (and mental health in general) within inpatient and outpatient rehabilitation programs, and endorse referral to a mental health professional.31
To improve rates of intervention and recognition and given the identified impact of depression on orthopaedic outcomes, the acknowledged reluctance of physicians to intervene, and the insufficiency of physician education to improve rates of depression recognition and intervention, it is clear that support for physicians to intervene with their depressed patients is needed. The authors hypothesized that an electronic medical record (EMR) alert and attendant protocol would catalyze surgeon-initiated intervention with patients with severe depression. The purpose of this study was to evaluate the efficacy of this simple intervention.
MATERIALS AND METHODS
Ethical Review and Study Design
Ethical review of this study was not obtained since all data were deidentified. Since this was a quality improvement effort and all analyzed data were anonymized, the study was not considered human subjects research and was exempt from review by the review board of the authors’ institution.
In March 2018 the authors routinely began collecting PROMIS Physical Function (PF), Pain Interference (PI), and Depression (D) Computer Adaptive Tests (CAT) at Cedars-Sinai Medical Center Orthopaedic Center and Spine Center outpatient clinics (OC) at each patient visit. The clinics service 50 providers and handle 56,000 visits per year. Early review of the data showed PROMIS CATs had been completed for 85% of the visits (N=2516) to the OC and 2% (N=56) of patients scored in the severe depression range. The magnitude of the problem became even more evident when the authors found an additional 16% (N=402) had scores indicating moderate depression. To ensure that surgeons were aware of who among their patients had scores indicating severe depression, a best practice alert was built into the EMR in October 2018. The alert fires in Epic, the authors’ health information software, when patient depression (D)-CAT scores indicate severe depression. It is sent to a triage nurse, who sends a message informing the treating surgeon about the patient depression status; the accompanying protocol suggests interventions (eg, talking points, referrals for mental-health follow-up are encouraged) and requests documentation in the EMR noting how and if the depression was addressed.
To discern the impact of the EMR alert and protocol on rates of intervention, the authors conducted a retrospective record review of all patients with a PROMIS-D score indicative of severe depression (total score 70+). Items verified in the chart were: if and where the patient was referred for follow-up; whether there was documentation regarding intervention or D-CAT score (Y/N); whether D-CAT score was referenced in progress note (Y/N); date of progress note, if different from encounter date; and was PRO smart-phrase used (Y/N).
Figure 1 shows that among 49,101 patient visits to the OC from October 1, 2018, through 2020, 60% (N=29,250) completed the PROMIS-D questionnaire. Among the visits with completed questionnaires, 1% (N=361) reflected scores of 70 or greater, indicative of severe depression. Review of OC patient EMR progress notes for the study period showed that surgeons documented some response to the best practice alert in only 28.5% (N=103) of the patient EMR with qualifying PROMIS CAT scores, 85% (N=88) of whom were referred for mental health follow-up to a mental health professional or their primary care provider (PCP) (Table 1).
TABLE 1 -
Where severely depressed patients who received physician-initiated intervention were referred
||Qualifying EMR with intervention (N=103) N (%)
||All qualifying EMR (N=361) %
| None/not specified
| Mental health provider
| Primary care physician
| Social worker
EMR, electronic medical record.
A growing body of research demonstrates that depression can greatly affect the outcomes of orthopaedic interventions, including having adverse effects related to pain, extent of disability, and physical function.10,20,21 Further, depressed patients have increased odds of postoperative complications, prolonged rehabilitation, and long-term dissatisfaction.11–18 Given this, it is important that health care professionals recognize depression along with patients’ specific musculoskeletal/orthopaedic complaints and, where it may be necessary, intervene. To aid in detection of patients suffering from depression in orthopaedic populations, and to support physician intervention with indicated patients, use of the PROMIS-D item bank is becoming widespread. In 2018, after the authors instituted routine collection of PROMIS data, including the PROMIS-D CAT, a best practice alert was built into the EMR to notify physicians of their patients whose PROMIS-D scores indicated severe depression.
The finding that the best practice alert prompted a documented response in less than one-third of the indicated cases comports with findings from studies aimed at improving physician-intervention for depression. Studies of this nature show generally no differences in treatment of depression among physicians receiving best practice EMR alerts, EMR alerts plus treatment advice, education, clinical guidelines, or some combination of interventions compared to usual care.25,26,29,32 Still, among primary care physicians and general medical providers, EMR best practice alerts or educational interventions can effectively change clinical practice when the outcome targeted is within the scope of usual care.33–39
The authors’ finding that most often the documentation in the EMR said the patient was referred to a mental health provider was not surprising since referral for follow-up was suggested in the information that accompanied the alert. That said, clinical practice guidelines for treating depression in outpatient medical clinics recommend referral to social work for further assessment and linkage to care or an alternative mental health professional for psychotherapy and potential recommendation of psychopharmacology support, as a best practice approach.40–42 Particular concern is mental health provider availability and the separation of mental health support from medical clinics, even though mental health and physical conditions are interrelated.41,43 Consideration for on-site social work or other mental health professionals may promote an interdisciplinary, collaborative approach to patient care and case management, which can reduce stigma and address the full scope of health and recovery, thus improving surgical outcomes.42,44
Finally, the sample was entirely from outpatient clinics at the authors’ institution. The consequent rapid flow of patients and pressures associated with expectations for quick room-turnover times could partially explain the findings of low adherence and brevity of EMR notations. In other words, pressures related to practicing in an OC could easily take priority over intervening with a patient about his or her mental health, especially since the pressures are shared by all practitioners, likely require less time, do not result in discomfort for patient or practitioner, nor potentially damage the patient-provider relationship.
One promise that the advent of widespread PROMIS data collection in orthopaedic clinics seems to hold is the achievement of improved clinical outcomes without the need for supplementary physician education or training. This becomes imaginable when one considers that a single, often published threshold, score or combination of scores can be used accurately to identify patients with the highest probability (or lowest) to benefit from a given treatment and predict the relative magnitude of the benefit. Acknowledgment of the low rates of depression recognition and intervention in the field are well known and the low rates found in this study are not unique. Research on how to improve rates of physician-initiated intervention is thus a burgeoning area of study. General discomfort with the subject matter and low self-efficacy to communicate effectively on the subject without harming their relationships with patients, predicated largely from reliance on a biomedical (vs. biopsychosocial) framework have been postulated as factors impacting musculoskeletal/orthopaedic specialists’ decision not to discuss the connection between depression and orthopaedic outcomes; initial investigation bears this out.45 Lending support to this theory, one study found nearly one-third of physicians reported when they recognized major depression in their patients they intentionally miscoded it, with most citing uncertainty regarding diagnosis and issues related to reimbursement as reasons.46 It is reasonable to infer that underlying the stated reasons could be the fear of having to have at least one difficult conversation with the potential to damage the patient-provider relationship.
Limitations and Future Perspectives
The major limitation of this study is that the authors only knew if the surgeon addressed the depression if they documented it in the patient’s EMR. It was possible that the surgeons did discuss depression with their patient and simply did not document it. While the response to the best practice alert disappointed the authors, they did not have data indicating rates of intervention before implementation of PROMIS data collection for comparison. Further, they did not accompany the alert with a concurrent effort to encourage physicians to intervene, and depression management is outside the scope of typical orthopaedic expertise. However, even with a physician’s referral, it is often difficult for patients to secure the mental-health follow-up. To better address depression in patients and aid in securing their follow-up, it might be important to imbed mental health professionals as well as a social worker who can assist with care coordination and brief intervention in the orthopaedic clinic as standard operating procedure to ensure that mental health is addressed in orthopaedics as a standard of care. Also, to identify differences in intervention rates and treatment response, individual-level characteristics could be investigated among both patients and providers.
Notification of patient depression-status alone was insufficient to persuade most surgeons to discuss the importance of mental health as it relates to their treatment, with their indicated patients; thus, a more comprehensive approach may be needed. To empower surgeons to have these conversations, extant barriers need be identified and addressed. One way to do this would be to ascertain the doctors’ concerns, perceived barriers, and recommendations for interventions they believe ultimately would be most effective in addressing those concerns. A component of any intervention could be the opportunity to practice communicating about this topic, even if the full extent of the desired intervention is to hand off the patient to a social worker who can assess their needs and facilitate continued care, if warranted. A social worker dedicated to the orthopaedic practice or clinic could simultaneously diminish related physician anxiety and improve patient mental health and thereby appropriateness for surgery.
1. Kroenke K, Stump TE, Chen CX, et al. Minimally important differences and severity thresholds are estimated for the PROMIS depression scales from three randomized clinical trials. J Affect Disord. 2020; 266:100–108.
2. Bernstein DN, Mayo K, Baumhauer JF, et al. Do patient sociodemographic factors impact the PROMIS scores meeting the patient-acceptable symptom state at the initial point of care in orthopaedic
foot and ankle patients? Clin Orthop. 2019; 477:2555–2565.
3. Rothrock NE, Kaat AJ, Vrahas MS, et al. Validation of PROMIS physical function instruments in patients with an orthopaedic
trauma to a lower extremity. J Orthop Trauma. 2019; 33:377–383.
4. Rose M, Bjorner JB, Gandek B, et al. The PROMIS physical function item bank was calibrated to a standardized metric and shown to improve measurement efficiency. J Clin Epidemiol. 2014; 67:516–526.
5. Cella D, Riley W, Stone A, et al. The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. J Clin Epidemiol. 2010; 63:1179–1194.
6. Horn ME, Reinke EK, Couce LJ, et al. Reporting and utilization of Patient-Reported Outcomes Measurement Information System® (PROMIS®) measures in orthopedic research and practice: a systematic review. J Orthop Surg. 2020; 15:553.
7. Hancock KJ, Glass N, Anthony CA, et al. PROMIS: a valid and efficient outcomes instrument for patients with ACL tears. Knee Surg Sports Traumatol Arthrosc. 2019; 27:100–104.
8. Anderson MR, Houck JR, Saltzman CL, et al. Validation and generalizability of preoperative PROMIS scores to predict postoperative success in foot and ankle patients. Foot Ankle Int. 2018; 39:763–770.
9. Kaat AJ, Buckenmaier CT, Cook KF, et al. The expansion and validation of a new upper extremity item bank for the Patient-Reported Outcomes Measurement Information System® (PROMIS). J Patient-Rep Outcomes. 2019; 3:69.
10. Vranceanu A-M, Barsky A, Ring D. Psychosocial aspects of disabling musculoskeletal pain. J Bone Joint Surg Am. 2009; 91:2014–2018.
11. Ali A, Lindstrand A, Sundberg M, et al. Preoperative anxiety and depression correlate with dissatisfaction after total knee arthroplasty: a prospective longitudinal cohort study of 186 patients, with 4-year follow-up. J Arthroplasty. 2017; 32:767–770.
12. Browne JA, Sandberg BF, D’Apuzzo MR, et al. Depression is associated with early postoperative outcomes following total joint arthroplasty: a nationwide database study. J Arthroplasty. 2014; 29:481–483.
13. Cho C-H, Seo H-J, Bae K-C, et al. The impact of depression and anxiety on self-assessed pain, disability, and quality of life in patients scheduled for rotator cuff repair. J Shoulder Elbow Surg. 2013; 22:1160–1166.
14. Duivenvoorden T, Vissers MM, Verhaar JAN, et al. Anxiety and depressive symptoms before and after total hip and knee arthroplasty: a prospective multicentre study. Osteoarthritis Cartilage. 2013; 21:1834–1840.
15. Stundner O, Kirksey M, Chiu YL, et al. Demographics and perioperative outcome in patients with depression and anxiety undergoing total joint arthroplasty: a population-based study. Psychosomatics. 2013; 54:149–157.
16. Werner BC, Wong AC, Chang B, et al. Depression and patient-reported outcomes following total shoulder arthroplasty. J Bone Joint Surg Am. 2017; 99:688–695.
17. Mollon B, Mahure SA, Ding DY, et al. The influence of a history of clinical depression on peri-operative outcomes in elective total shoulder arthroplasty. Bone Joint J. 2016; 98-B:818–824.
18. Martin RL, Christoforetti JJ, McGovern R, et al. The impact of depression on patient outcomes in hip arthroscopic surgery. Orthop J Sports Med. 2018; 6:2325967118806490.
19. Saravay SM, Lavin M. Psychiatric comorbidity and length of stay in the general hospital: a critical review of outcome studies. Psychosomatics. 1994; 35:233–252.
20. Geisser ME, Robinson ME, Keefe FJ, et al. Catastrophizing, depression and the sensory, affective and evaluative aspects of chronic pain. Pain. 1994; 59:79–83.
21. Ring D, Kadzielski J, Fabian L, et al. Self-reported upper extremity health status correlates with depression. J Bone Joint Surg Am. 2006; 88:1983–1988.
22. Vajapey SP, McKeon JF, Krueger CA, et al. Outcomes of total joint arthroplasty in patients with depression: a systematic review. J Clin Orthop Trauma. 2021; 18:187–198.
23. Ho B, Houck JR, Flemister AS, et al. Preoperative PROMIS scores predict postoperative success in foot and ankle patients. Foot Ankle Int. 2016; 37:911–918.
24. Rosenberger PH, Jokl P, Ickovics J. Psychosocial factors and surgical outcomes: an evidence-based literature review. J Am Acad Orthop Surg. 2006; 14:397–405.
25. Lin EHB, Simon GE, Katzelnick DJ, et al. Does physician education on depression management improve treatment in primary care? J Gen Intern Med. 2001; 16:614–619.
26. Schulberg HC, Block MR, Madonia MJ, et al. The “usual care” of major depression in primary care practice. Arch Fam Med. 1997; 6:334–339.
27. Forsetlund L, Bjørndal A, Rashidian A, et al. Continuing education meetings and workshops: effects on professional practice and health care outcomes. Cochrane Database Syst Rev. 2009; 2:CD003030.
28. Lauria-Horner B, Beaulieu T, Knaak S, et al. Controlled trial of the impact of a BC adult mental health practice support program (AMHPSP) on primary health care professionals’ management of depression. BMC Fam Pract. 2018; 19:183.
29. Thompson C, Kinmonth A, Stevens L, et al. Effects of a clinical-practice guideline and practice-based education on detection and outcome of depression in primary care: Hampshire Depression Project randomised controlled trial. Lancet. 2000; 355:185–191.
30. Lee S-J, Nam T-W, Kim C-H, et al. Knowledge and attitude of nonpsychiatric physicians regarding suicide in spinal cord injury patients and need for structured psychiatric education for suicide prevention: A prospective survey pilot study. Medicine (Baltimore). 2019; 98:e14901.
31. Management of mental health disorders, substance use disorders, and suicide in adults with spinal cord injury. J Spinal Cord Med. 2021; 44:102–162.
32. Rollman BL, Hanusa BH, Gilbert T, et al. The electronic medical record: a randomized trial of its impact on primary care physicians’ initial management of major depression. Arch Intern Med. 2001; 161:189–197.
33. Konerman MA, Thomson M, Gray K, et al. Impact of an electronic health record alert in primary care on increasing hepatitis c screening and curative treatment for baby boomers. Hepatology. 2017; 66:1805–1813.
34. Barnes GD, Spranger E, Sippola E, et al. Assessment of a best practice alert and referral process for preprocedure antithrombotic medication management for patients undergoing gastrointestinal endoscopic procedures. JAMA Netw Open. 2020; 3:e1920548.
35. Najafi N, Cucina R, Pierre B, et al. Assessment of a targeted electronic health record intervention to reduce telemetry duration: a cluster-randomized clinical trial. JAMA Intern Med. 2019; 179:11–15.
36. Lee J, Szeto L, Pasupula DK, et al. Cluster randomized trial examining the impact of automated best practice alert on rates of implantable defibrillator therapy. Circ Cardiovasc Qual Outcomes. 2019; 12:e005024.
37. Hsiang EY, Mehta SJ, Small DS, et al. Association of an active choice intervention in the electronic health record directed to medical assistants with clinician ordering and patient completion of breast and colorectal cancer screening tests. JAMA Netw Open. 2019; 2:e1915619.
38. Okoli GN, Reddy VK, Lam OLT, et al. Interventions on health care providers to improve seasonal influenza vaccination rates among patients: a systematic review and meta-analysis of the evidence since 2000. Fam Pract. 2021; 38:524–536.
39. Kwan JL, Lo L, Ferguson J, et al. Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials. BMJ. 2020; 370:m3216.
40. Petterson S, Miller BF, Payne-Murphy JC, et al. Mental health treatment in the primary care setting: patterns and pathways. Fam Syst Health. 2014; 32:157–166.
41. Unützer J, Schoenbaum M, Druss BG, et al. Transforming mental health care at the interface with general medicine: report for the presidents commission. Psychiatr Serv. 2006; 57:37–47.
42. Coleman J, Patrick D. Integrating mental health services into primary medical care. Med Care. 1976; 14:654–661.
43. Thielke S, Vannoy S, Unützer J. Integrating mental health and primary care. Prim Care. 2007; 34:571–592.
44. Patterson J, Peek CJ, Heinrich RL, et al. Mental Health Professionals in Medical Settings: A Primer. New York: WW Norton & Co; 2002:viii, 232.
45. Gonzalez AI, Kortlever JTP, Brown LE, et al. Can crafted communication strategies allow musculoskeletal specialists to address health within the biopsychosocial paradigm? Clin Orthop Relat Res. 2021; 479:1217–1223.
46. Rost K. The deliberate misdiagnosis of major depression in primary care. Arch Fam Med. 1994; 3:333–337.