Pre-Operative Testing for Cataract Surgery
Conditions
Keywords
Low Value Care, Cataract Surgery, Behavioral Economics
Brief summary
There is strong consensus - based on robust randomized trial data - that routine pre-operative (pre-op) testing for cataract surgery is inappropriate. Despite these widely endorsed evidence-based recommendations, most seniors undergoing cataract surgery still receive unnecessary blood testing, EKGs, and chest X-rays (CXRs); another substantial percentage even undergo nonindicated cardiac stress tests. We will integrate three new best practice alert (BPA) nudges into the University of California, Los Angeles (UCLA) Health electronic health record (EHR). The nudges are informed by behavioral economic theory and are designed to alter the choice architecture for physicians to decrease the rate of pre-op test ordering while still preserving clinician autonomy. We will conduct a pragmatic trial to evaluate whether these BPA nudges reduce low-value pre-op testing for cataract surgery.
Detailed description
There is strong consensus - based on robust randomized trial data - that routine pre-operative (pre-op) testing for cataract surgery is inappropriate (Keay et al, 2009; Keay et al, 2012; Schein et al, 2000; Chen et al, 2015). Because pre-op testing provides no benefit to patients, the American Academy of Ophthalmology named reducing routine pre-op testing for cataract surgery the #1 issue that patients and physicians should question as part of the Choosing Wisely™ campaign (Schein et al, 2012). Despite these widely endorsed evidence-based recommendations, most seniors undergoing cataract surgery still receive unnecessary blood testing, EKGs, and chest X-rays (CXRs); another substantial percentage even undergo non-indicated cardiac stress tests (Rumball-Smith et al, 2017). With cataract surgery being the most common medical procedure among Medicare beneficiaries (predicted 4.4 million per year by the year 2030) (Schein et al, 2012), widespread reduction of routine pre-op testing for cataract surgery would reduce costs, reduce exposure to unnecessary and potentially harmful tests, and allow millions of seniors to spend more time enjoying life rather than wasting their time receiving inappropriate health care. The investigators hypothesize that an interdisciplinary electronic health record (EHR)-based intervention that applies behavioral economics approaches (i.e., nudges) will dramatically reduce pre-op testing for cataract surgery in a real-world clinical setting. The investigators propose to test this hypothesis by conducting a pragmatic randomized trial, implementing this intervention at UCLA Health (Ronald Reagan UCLA Medical Center), where \ 3200 cataract surgeries are performed per year. The specific aims are to: 1. Integrate three new BPA nudges into the UCLA Health EHR. The investigators will conduct a four-arm randomized pragmatic trial to compare the effectiveness of the nudges vs. usual care. Three distinct nudges were tailored to highlight the safety aspects of pre-op tests, the financial harms to the patient of experiencing pre-op tests, and the potential psychological harms to the patient of experiencing preop tests. The pragmatic trial will include three types of behavioral nudges to promote the desired reduction in low value care: Nudge 1: * UCLA Ophthalmologists and Anesthesiologists ADVISE AGAINST routine pre-op testing. * UCLA Pre-op Eval and Planning Center (PEPC) will order any needed labs on the day of surgery. * Routine pre-op tests are inappropriate. * Routine pre-op tests do NOT increase patient safety and go AGAINST local and national guidelines * Hard stop before allowing the ordering of a pre-op test where physicians must provide accountable justification: EXPLAIN WHY GOING AGAINST GUIDELINES Nudge 2: * UCLA Ophthalmologists and Anesthesiologists ADVISE AGAINST routine pre-op testing. * UCLA Pre-op Eval and Planning Center (PEPC) will order any needed labs on the day of surgery. * Routine pre-op tests are inappropriate. * Routine pre-operative tests can increase the patient's out-of-pocket costs without improving the safety or medical outcomes of cataract surgery and go AGAINST local and national guidelines * Hard stop before allowing the ordering of a pre-op test where physicians must provide accountable justification: EXPLAIN WHY GOING AGAINST GUIDELINES Nudge 3: * UCLA Ophthalmologists and Anesthesiologists ADVISE AGAINST routine pre-op testing. * UCLA Pre-op Eval and Planning Center (PEPC) will order any needed labs on the day of surgery. * Routine pre-op tests are inappropriate. * Routine pre-operative tests can cause aggravation and psychological stress for the patient without improving the safety or medical outcomes of cataract surgery and go AGAINST local and national guidelines * Hard stop before allowing the ordering of a pre-op test where physicians must provide accountable justification: EXPLAIN WHY GOING AGAINST GUIDELINES 2. Randomize providers who conducted a pre-op visit in 2019 and those who are expected to conduct such a visit during the 12-month study period to one of 4 study arms (usual pre-op care, Nudge #1, Nudge #2, or Nudge #3) and measure and compare the efficacy of each intervention. The investigators will measure and compare rates of testing before and after initiation of the randomization. Outcomes will be measured 12-months after the intervention start date. For the primary outcome, we will assess the change in the percentage of cataract patients who undergo one or more pre-op tests after 12 months, where the baseline comparison will be 2019. While we intended to the 12-month pre-period as the baseline, the COVID-19 pandemic had a substantial impact on cataract surgeries. We will compare the percentage of patients receiving pre-op testing in the pooled nudge arms to the usual care arm (primary outcome) and measure the efficacy of each individual nudge arm to determine whether certain behavioral economic framing techniques are more effective than others at reducing pre-op testing (secondary outcomes). Other secondary outcomes will include the change in the percentage of patients who received pre-op labs, pre-op EKGs, and pre-op CXRs. We will also evaluate the total number of pre-op tests patients received, same-day surgery cancellations, cost savings to the health system, and cost savings to the patient. To elicit the views and experiences of physicians, we will survey physicians randomized to all intervention arms to evaluate their experience with the EHR alerts. Reducing patient exposure to unnecessary care is central to improving patient outcomes and value. This project is fully aligned with UCLA Health leadership's current priority of supporting cross-departmental system change to improve quality of care, outcomes, and value for UCLA patients. Because of the close partnership between our UCLA Informatics co-Investigators and the EHR vendor (Epic), the low-cost intervention that we propose to implement and test will be easily disseminatable to all Epic-based health systems, and will have the potential to dramatically reduce inappropriate pre-op testing across the nation. EHRs are in their infancy, and the scientific community is only beginning to learn how to use them as tools to promote desired care processes (Meeker et al, 2016). This proposed pragmatic trial would break new ground in our understanding of how behavioral economics approaches can be used to tamp down on care that does not promote better patient outcomes.
Interventions
Nudge 1: * UCLA Ophthalmologists and Anesthesiologists ADVISE AGAINST routine pre-op testing. * UCLA Pre-op Eval and Planning Center (PEPC) will order any needed labs on the day of surgery. * Routine pre-op tests are inappropriate. * Routine pre-op tests do NOT increase patient safety and go AGAINST local and national guidelines Hard stop before allowing the ordering of a pre-op test where physicians must provide accountable justification: EXPLAIN WHY GOING AGAINST GUIDELINES
Nudge #2: * UCLA Ophthalmologists and Anesthesiologists ADVISE AGAINST routine pre-op testing. * UCLA Pre-op Eval and Planning Center (PEPC) will order any needed labs on the day of surgery. * Routine pre-op tests are inappropriate. * Routine pre-operative tests can increase the patient's out-of-pocket costs without improving the safety or medical outcomes of cataract surgery and go AGAINST local and national guidelines * Nudge includes hard stop before allowing the ordering of a pre-op test where physicians must provide accountable justification: EXPLAIN WHY GOING AGAINST GUIDELINES
Nudge 3: * UCLA Ophthalmologists and Anesthesiologists ADVISE AGAINST routine pre-op testing. * UCLA Pre-op Eval and Planning Center (PEPC) will order any needed labs on the day of surgery. * Routine pre-op tests are inappropriate. * Routine pre-operative tests can cause aggravation and psychological stress for the patient without improving the safety or medical outcomes of cataract surgery and go AGAINST local and national guidelines * Hard stop before allowing the ordering of a pre-op test where physicians must provide accountable justification: EXPLAIN WHY GOING AGAINST GUIDELINES
Patients will receive usual care from their physicians.
Sponsors
Study design
Eligibility
Inclusion criteria
* Patient at UCLA undergoing cataract surgery, and receives pre-operative evaluation at UCLA Health
Exclusion criteria
* Cataract surgery patients who get their pre-operative evaluation from non-UCLA physicians
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Pre-Operative Testing Change | Pre-intervention (Baseline), Post-Intervention (12 months) | Change in percentage of patients undergoing pre-operative testing (labs, EKG, CXR) |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Pre-Operative Testing Change for Specific Categories of Tests | Pre-intervention (Baseline), Post-Intervention (12 months) | Change in the percentage of patients who received pre-op labs, pre-op EKGs, and pre-op chest x-rays (CXRs). |
| Physician Experience Survey Results | Post-Intervention (12 months) | Perceived change in workflow, autonomy, satisfaction (Modified Survey) |
| Pre-Operative Testing Change | Pre-intervention (Baseline), Post-Intervention (12 months) | Efficacy of each individual nudge arm compared with usual care to determine whether certain behavioral economic framing techniques are more effective than others at reducing pre-op testing. |
| System-level Change - Cost Savings | Pre-intervention (Baseline), Post-Intervention (12 months) | Analysis of costs saved for enrolled participants |
| System-level Change - Return on Investment | Pre-intervention (Baseline), Post-Intervention (12 months) | Analysis of cost savings to the health system assuming a reduction of tests being ordered |
| System-level Change - Surgery Cancellations | Baseline, 12 months | Analysis of day of surgery cancellations for enrolled participants |
Countries
United States
Participant flow
Pre-assignment details
Participants were enrolled into the study when they have a pre-operative encounter for cataract surgery AND the physician starts to order a pre-op lab. Eligible providers were assigned an arm of the study based on their 2019 pre-operative visits. Patients were enrolled into each arm based on the providers arm assignment. Healthcare Providers were not enrolled in the study
Participants by arm
| Arm | Count |
|---|---|
| Alert 1 Patients with a pre-op encounter in which the physician attempts to place an order for a pre-op test. Physician has been assigned to the Nudge #1 group.
Nudge #1: Alert highlighting the safety/potential harms to patients of undergoing pre-op tests: Nudge 1:
* UCLA Ophthalmologists and Anesthesiologists ADVISE AGAINST routine pre-op testing.
* UCLA Pre-op Eval and Planning Center (PEPC) will order any needed labs on the day of surgery.
* Routine pre-op tests are inappropriate.
* Routine pre-op tests do NOT increase patient safety and go AGAINST local and national guidelines Hard stop before allowing the ordering of a pre-op test where physicians must provide accountable justification: EXPLAIN WHY GOING AGAINST GUIDELINES | 269 |
| Alert 2 Patients with a pre-op encounter in which the physician attempts to place an order for a pre-op test. Physician has been assigned to the Nudge #2 group
Nudge #2: Alert highlighting the financial harms to the patient experiencing pre-op tests: Nudge #2:
* UCLA Ophthalmologists and Anesthesiologists ADVISE AGAINST routine pre-op testing.
* UCLA Pre-op Eval and Planning Center (PEPC) will order any needed labs on the day of surgery.
* Routine pre-op tests are inappropriate.
* Routine pre-operative tests can increase the patient's out-of-pocket costs without improving the safety or medical outcomes of cataract surgery and go AGAINST local and national guidelines
* Nudge includes hard stop before allowing the ordering of a pre-op test where physicians must provide accountable justification: EXPLAIN WHY GOING AGAINST GUIDELINES | 267 |
| Alert 3 Patients with a pre-op encounter in which the physician attempts to place an order for a pre-op test. Physician has been assigned to the Nudge #3 group
Nudge #3: Alert highlighting potential psychological harms to the patient of experiencing pre-op tests: Nudge 3:
* UCLA Ophthalmologists and Anesthesiologists ADVISE AGAINST routine pre-op testing.
* UCLA Pre-op Eval and Planning Center (PEPC) will order any needed labs on the day of surgery.
* Routine pre-op tests are inappropriate.
* Routine pre-operative tests can cause aggravation and psychological stress for the patient without improving the safety or medical outcomes of cataract surgery and go AGAINST local and national guidelines
* Hard stop before allowing the ordering of a pre-op test where physicians must provide accountable justification: EXPLAIN WHY GOING AGAINST GUIDELINES | 272 |
| Control Patients with a pre-op encounter in which the physician attempts to place an order for a pre-op test. Physician has been assigned to the Control group.
Usual Care: Patients will receive usual care from their physicians. | 237 |
| Total | 1,045 |
Baseline characteristics
| Characteristic | Alert 1 | Alert 2 | Alert 3 | Control | Total |
|---|---|---|---|---|---|
| Age, Continuous | 71.07 years STANDARD_DEVIATION 9.58 | 72.00 years STANDARD_DEVIATION 10.98 | 72.98 years STANDARD_DEVIATION 9.61 | 72.27 years STANDARD_DEVIATION 10.24 | 72.08 years STANDARD_DEVIATION 9.37 |
| Ethnicity (NIH/OMB) Hispanic or Latino | 28 Participants | 34 Participants | 38 Participants | 26 Participants | 126 Participants |
| Ethnicity (NIH/OMB) Not Hispanic or Latino | 214 Participants | 203 Participants | 204 Participants | 178 Participants | 799 Participants |
| Ethnicity (NIH/OMB) Unknown or Not Reported | 27 Participants | 30 Participants | 30 Participants | 33 Participants | 120 Participants |
| Race/Ethnicity, Customized EthnoRacial Category Asian | 33 Participants | 45 Participants | 31 Participants | 24 Participants | 133 Participants |
| Race/Ethnicity, Customized EthnoRacial Category Black or African American | 20 Participants | 11 Participants | 18 Participants | 18 Participants | 67 Participants |
| Race/Ethnicity, Customized EthnoRacial Category Hispanic or Latino | 26 Participants | 32 Participants | 37 Participants | 26 Participants | 121 Participants |
| Race/Ethnicity, Customized EthnoRacial Category Middle Eastern or North African | 7 Participants | 4 Participants | 5 Participants | 5 Participants | 21 Participants |
| Race/Ethnicity, Customized EthnoRacial Category Multiple Ethnoracial Categories | 5 Participants | 3 Participants | 3 Participants | 2 Participants | 13 Participants |
| Race/Ethnicity, Customized EthnoRacial Category Native Hawaiian or Other Pacific Islander | 0 Participants | 0 Participants | 1 Participants | 1 Participants | 2 Participants |
| Race/Ethnicity, Customized EthnoRacial Category Unknown or Not Reported | 36 Participants | 40 Participants | 29 Participants | 30 Participants | 135 Participants |
| Race/Ethnicity, Customized EthnoRacial Category White | 142 Participants | 132 Participants | 148 Participants | 131 Participants | 553 Participants |
| Sex: Female, Male Female | 168 Participants | 140 Participants | 161 Participants | 126 Participants | 595 Participants |
| Sex: Female, Male Male | 101 Participants | 127 Participants | 111 Participants | 111 Participants | 450 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk | EG002 affected / at risk | EG003 affected / at risk |
|---|---|---|---|---|
| deaths Total, all-cause mortality | 1 / 269 | 3 / 267 | 0 / 272 | 2 / 237 |
| other Total, other adverse events | 9 / 269 | 7 / 267 | 12 / 272 | 12 / 237 |
| serious Total, serious adverse events | 11 / 269 | 4 / 267 | 4 / 272 | 12 / 237 |
Outcome results
Pre-Operative Testing Change
Change in percentage of patients undergoing pre-operative testing (labs, EKG, CXR)
Time frame: Pre-intervention (Baseline), Post-Intervention (12 months)
Population: The participants in this study are UCLA Health physicians who complete a pre-op visit for at least one patient undergoing cataract surgery at UCLA in the 12 months prior and 12 months after the study start date and all patients who are seen during such visits.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| Alert 1 | Pre-Operative Testing Change | Pre | 87.4 Percentage of patients with orders | Standard Deviation 33.2 |
| Alert 1 | Pre-Operative Testing Change | Post | 84.6 Percentage of patients with orders | Standard Deviation 36.2 |
| Alert 2 | Pre-Operative Testing Change | Post | 80.3 Percentage of patients with orders | Standard Deviation 39.9 |
| Alert 2 | Pre-Operative Testing Change | Pre | 85.0 Percentage of patients with orders | Standard Deviation 35.8 |
| Alert 3 | Pre-Operative Testing Change | Pre | 86.1 Percentage of patients with orders | Standard Deviation 34.6 |
| Alert 3 | Pre-Operative Testing Change | Post | 79.8 Percentage of patients with orders | Standard Deviation 40.3 |
| Control | Pre-Operative Testing Change | Pre | 85.4 Percentage of patients with orders | Standard Deviation 35.4 |
| Control | Pre-Operative Testing Change | Post | 83.5 Percentage of patients with orders | Standard Deviation 37.2 |
Physician Experience Survey Results
Perceived change in workflow, autonomy, satisfaction (Modified Survey)
Time frame: Post-Intervention (12 months)
Pre-Operative Testing Change
Efficacy of each individual nudge arm compared with usual care to determine whether certain behavioral economic framing techniques are more effective than others at reducing pre-op testing.
Time frame: Pre-intervention (Baseline), Post-Intervention (12 months)
Pre-Operative Testing Change for Specific Categories of Tests
Change in the percentage of patients who received pre-op labs, pre-op EKGs, and pre-op chest x-rays (CXRs).
Time frame: Pre-intervention (Baseline), Post-Intervention (12 months)
System-level Change - Cost Savings
Analysis of costs saved for enrolled participants
Time frame: Pre-intervention (Baseline), Post-Intervention (12 months)
System-level Change - Return on Investment
Analysis of cost savings to the health system assuming a reduction of tests being ordered
Time frame: Pre-intervention (Baseline), Post-Intervention (12 months)
System-level Change - Surgery Cancellations
Analysis of day of surgery cancellations for enrolled participants
Time frame: Baseline, 12 months