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Record W2915150188 · doi:10.1213/ane.0000000000003973

I Can’t Get No (Patient) Satisfaction

2019· letter· en· W2915150188 on OpenAlexaffabout
Honorio T. Benzon, Lauren K. Dunn, De Q.H. Tran

Bibliographic record

VenueAnesthesia & Analgesia · 2019
Typeletter
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicinePatient satisfactionAnxietyRegimenAnalgesicDepression (economics)Patient experiencePhysical therapyHealth carePsychiatrySurgery

Abstract

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Increasingly, patient satisfaction constitutes a measured outcome in published medical trials.1,2 In this issue of the Journal, Siu et al3 prospectively investigated determinants of patient satisfaction with postoperative pain management after video-assisted thoracoscopic surgery. The authors surveyed 300 patients using a modified questionnaire that assessed multidimensional factors including pain scores, psychological factors (ie, anxiety and depression), activities (ie, ambulation and sleep), medication-related side effects, patient information, and involvement in decision-making. The ability to participate in analgesic decisions was found to be the most reliable predictor of patient satisfaction. Other positive predictors included the provision of information regarding treatment options, while pain intensity and interference with sleep constituted negative determinants. Despite its apparent simplicity, the term “patient satisfaction” can be riddled with ambiguity, as medical care represents a multidimensional experience, with each individual facet giving rise to varying levels of satisfaction (or dissatisfaction) among patients. Siu et al3 minimized the potential semantic trap by focusing their study on satisfaction pertaining to acute pain management, focusing on postoperative days 1 and 2. They did not assess patient satisfaction with chronic postsurgical pain, which may be related to a higher degree of dissatisfaction, influenced by different factors, and subject to different treatments. Patient satisfaction with acute pain management encompasses 2 distinct elements: satisfaction with the outcome (ie, the success of the pain regimen) and with the process itself (ie, the collective effort to achieve analgesia). Although overlap exists, the 2 components should be viewed as separate entities. For example, a patient could receive inadequate pain control but be thankful for all the attempts/information provided to ensure optimal analgesia.1 Conversely, a patient with minimal postoperative pain could be unsatisfied due to his or her paternalistic exclusion from the decision-making process.1 Although Siu et al3 did not explicitly differentiate between the 2 components, their questionnaire contained elements related to both outcome (eg, questions 1–6 and 12) and process (eg, questions 7, 8, 10, and 11). The results by Siu et al3 echo those of Caljouw et al,4 who previously noted that satisfaction was dependent not only on anesthetic outcome but also on how patients were approached and the information that they received. Together, these 2 studies highlight the fact that process-related factors (eg, participation in decisional process) may be as, or even more, important than outcome-based parameters (ie, pain intensity) in ensuring patient satisfaction. These findings mirror conclusions previously published in the surgical literature. For instance, after hand surgery, improvement in strength, range of motion, and activities of daily living emerged as major predictors of satisfaction.2 However, in addition to these outcome-related factors, process-based parameters appear critical to surgical patients, because patient information, shared decision making, length of follow-up, duration of waiting time, state of facility, and food can significantly impact patient satisfaction.2 Moreover, a surgeon’s perceived empathy has been intimately linked to his or her patients’ contentment. Outcome- and process-related determinants both fall under the control of health care providers. Thus, it may be tempting to believe that physicians can become the sole architects of patient satisfaction. Unfortunately, evidence shows that satisfaction also depends on patient-related factors that can escape medical control (Table).5 For example, in a recent observational study, patient-related sociodemographic variables such as male gender, older age, and higher education level were associated with increased satisfaction scores after anesthesia.6 Similar results were reported in a cross-sectional analysis of 16,222 patients undergoing nonobstetric surgery in the United Kingdom.7 Younger age, female gender, and obesity, as well as histories of stroke, neuropathic pain, and long-term opioid use, constituted nonmodifiable parameters associated with severe discomfort after surgery.Table.: Factors and Provider-Related Measures That Affect Patient SatisfactionOther patient-specific factors may be modifiable. For example, psychological traits (eg, anxiety, depression, and catastrophizing) can be alleviated by relaxation techniques, cognitive behavioral therapy, and an improvement in postoperative pain and recovery.7 In addition, independent of pain control, attention to patient comfort through simple measures, such as carbohydrate loading/early feeding, early mobilization, and limiting sleep interference, may also increase patient satisfaction. Therefore, as noted by Siu et al,3 patient education and preparation for surgery can play a role in promoting satisfaction. Although most researchers agree that patient satisfaction should be assessed in all trials investigating perioperative outcomes, one important piece of the puzzle often remains relegated to the realm of afterthought: the assessment of satisfaction itself. In other words, how does one reliably measure patient satisfaction? Within the specialty of anesthesiology, methods have ranged from user-friendly questionnaires to validated measurement tools. The Patient Global Impression of Change, a very popular tool, should be used parsimoniously, as it does not assess satisfaction per se. Instead, the patient simply comments on his or her overall status and whether the latter has changed, worsened, or remained status quo. Other simple measurement methods include satisfaction scores presented in the form of visual analog or Likert scale. Similar to Patient Global Impression of Change, the reliability of these rating systems remains poor, as they fail to capture the multidimensional and complex nature of satisfaction.1 Fortunately, more reliable tools have been devised (and validated) to assess patient satisfaction related to anesthetic management. They encompass the Iowa Satisfaction With Anesthesia Scale for monitored anesthesia care8 and the Scale of Patients’ Perceptions of Cardiac Anaesthesia Services after cardiac anesthesia.9 Sophisticated questionnaires developed for general noncardiac anesthesia include the Evaluation du Vécu de l’Anesthésie Générale questionnaire,10 Leiden Perioperative Care Patient Satisfaction questionnaire,4 Patient Satisfaction with Perioperative Anesthetic Care questionnaire,11 Anaesthesiological Questionnaire,12 and the Bauer questionnaire.13 The Evaluation du Vécu de l’Anesthésie Générale questionnaire consists of 26 questions pertaining to attention, privacy, information, pain, discomfort, waiting, and global impression.10 In contrast, the Bauer questionnaire includes 10 anesthesia-related questions pertaining to discomfort (eg, pain at surgical or injection site, sore throat, hoarseness, thirst, cold, and shivering) and 5 questions pertaining to satisfaction with preoperative information, emergence from anesthesia, pain, and overall anesthesia care.13 The 5 straightforward questions related to patient satisfaction may explain the selection of the Bauer questionnaire in a large cross-sectional study investigating the outcome of perioperative anesthesia in the United Kingdom.7 The psychometric properties of the validated instruments have been previously compared. The time required to complete the questionnaires usually ranges from 3 to 12 minutes.14 Expectedly, most tools are linguistically specific to the population for whom they were originally developed. For instance, the Anaesthesiological Questionnaire is in German and applies to German patients.12 However, tools such as the Leiden Perioperative Care Patient Satisfaction questionnaire, a Dutch questionnaire, have been translated and validated in the English language. Similarly, other validated methods used across Europe include the Evaluation du Vécu de l’Anesthésie Générale and Bauer questionnaires. In contrast, the Patient Satisfaction with Perioperative Anesthetic Care questionnaire, which was developed for Chinese Taiwanese patients, requires further investigation regarding its suitability for non-Chinese–speaking people from Asia, as well as English-speaking populations.11 While the previous questionnaires target patient satisfaction, there also exist validated multidimensional tools that include patient satisfaction as part of the overall assessment of pain management, such as the Revised American Pain Society Outcome Questionnaire15 and the International Pain Outcome Questionnaire.16 The Revised American Pain Society Outcome Questionnaire was created for quality improvement audits of pain management, while the International Pain Outcome, a modification of the Revised American Pain Society Outcome Questionnaire, was designed for postoperative application. Both the Revised American Pain Society Outcome Questionnaire and the International Pain Outcome questionnaire include a question on patient participation in the therapeutic decisional process. Furthermore, they both include all domains recommended by the Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials group (ie, pain, physical functioning, emotional functioning, side effects, and patient satisfaction). Interestingly, despite their frequent use and popularity, the different iterations of the Quality of Recovery questionnaire (ie, Quality of Recovery 40 and 15), Short-Form Health Survey (Short-Form Health Survey 36, 12, and 8), McGill Pain Questionnaire, Brief Pain Inventory, and European Quality of Life 5-Dimensions do not assess patient satisfaction per se. In their trial, Siu et al3 elected to forego the use of a simple score in favor of a modified version of the Revised American Pain Society Outcome Questionnaire. To improve the understandability of the latter, Siu et al3 altered 3 questions and added 2 new ones. Their modifications aimed to minimize responder confusion and thus appear reasonable. Nonetheless, the reader must be cognizant of the fact that this modified Revised American Pain Society Outcome Questionnaire requires further investigation before widespread implementation. Such clinical validation would need to show that the modified Revised American Pain Society Outcome Questionnaire (or at least its revised portions) fulfills all conditions of good psychometric questionnaire construction in terms of item generation process, pretest, pilot testing, revision, reliability, validity, and acceptability.1,14 In conclusion, patient satisfaction remains a barometer used by many hospitals to measure success, as well a driver of infrastructural changes. Successful pain management, a major perioperative determinant of patient satisfaction, should be the goal in every patient. Through the provision of optimal postoperative analgesia, as well as the improvement of functional outcomes (eg, quadriceps-sparing nerve blocks for total knee replacement), our specialty will play a vital role in upholding and promoting patient satisfaction. The implementation of an institution-wide quality management system for the treatment of postoperative pain, which includes structured patient information on postoperative pain management and treatment modalities, as well as a standardized multimodal analgesic regimen, can positively affect patient satisfaction. Such implementation will not only reduce postoperative pain but also improve patient satisfaction and quality of life. Thus, going forward, as anesthesiologists, we should not forget that we are perhaps the physicians best positioned to ensure satisfaction in all patients undergoing surgery. In our continued efforts to improve patient satisfaction, we must abide by the Rolling Stones’ counsel: “And (we) try and (we) try and (we) try…” DISCLOSURES Name: Honorio T. Benzon, MD. Contribution: This author helped write the manuscript. Conflicts ofInterest: H. T. Benzon is a member of the Advisory Board, Sandoz International. Name: Lauren K. Dunn, MD, PhD. Contribution: This author helped write the manuscript. Conflicts of Interest: None. Name: De Q. Tran, MD, FRCPC. Contribution: This author helped write the manuscript. Conflicts ofInterest: None. This manuscript was handled by: Jianren Mao, MD, PhD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.110
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.023
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.110
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0060.005
Open science0.0010.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0220.006

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.343
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations5
Published2019
Admission routes2
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