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OBJECTIVES: To assess the use of a co-designed patient-reported outcome (PRO) clinical dashboard and estimate its impact on shared decision-making (SDM) and symptomatology in adults with advanced cancer or chronic kidney disease (CKD). MATERIALS AND METHODS: We developed a clinical PRO dashboard within the Northwestern Medicine Patient-Reported Outcomes system, enhanced through co-design involving 20 diverse constituents. Using a single-group, pretest-posttest design, we evaluated the dashboard's use among patients with advanced cancer or CKD between June 2020 and January 2022. Eligible patients had a visit with a participating clinician, completed at least two dashboard-eligible visits, and consented to follow-up surveys. PROs were collected 72 h prior to visits, including measures for chronic condition management self-efficacy, health-related quality of life (PROMIS measures), and SDM (collaboRATE). Responses were integrated into the EHR dashboard and accessible to clinicians and patients. RESULTS: We recruited 157 participants: 66 with advanced cancer and 91 with CKD. There were significant improvements in SDM from baseline, as assessed by collaboRATE scores. The proportion of participants reporting the highest level of SDM on every collaboRATE item increased by 15 percentage points from baseline to 3 months, and 17 points between baseline and 6-month follow-up. Additionally, there was a clinically meaningful decrease in anxiety levels over study period (T-score baseline: 53; 3-month: 52; 6-month: 50; P < .001), with a standardized response mean (SRM) of -0.38 at 6 months. DISCUSSION: PRO clinical dashboards, developed and shared with patients, may enhance SDM and reduce anxiety among patients with advanced cancer and CKD.

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Objectives: Patient-reported outcomes (PROs) describe a patient's unique experiences with disease or treatment, yet effective use of this information during clinical encounters remains challenging. This project sought to build a PRO based dashboard within the electronic health record (EHR), prioritizing interpretability and utility of PROs for clinical decision-making. Materials and Methods: Codesign principles were used to define the goal, features, and visualization of the data elements on the dashboard. Codesign sessions occurred between February 2019 and May 2020 and involved a diverse group of stakeholders. Pilot evaluation of dashboard usability was performed with patients and clinicians not involved in the codesign process through qualitative interviews and the Systems Usability Scale. Results: The dashboard was placed into a single tab in the EHR and included select PROM scores, clinical data elements, and goals of care questions. Real-time data analytics and enhanced visualization of data was necessary for the dashboard to provide meaningful feedback to clinicians and patients for decision-making during clinic visits. During soft launch, the dashboard demonstrated "good" usability in patients and clinicians at 3 and 6 months (mean total SUS score >70). Discussion: The current dashboard had good usability and made PRO scores more clinically understandable to patients and clinicians. This paper highlights the development, necessary data elements, and workflow considerations to implement this dashboard at an academic cancer center. Conclusion: As the use of PROs in clinical care is increasing, patient- and clinician-centered tools are needed to ensure that this information is used in meaningful ways.

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Background: Shared decision making (SDM) is the process by which patients and clinicians exchange information and preferences to come to joint healthcare decisions. Clinical dashboards can support SDM by collecting, distilling, and presenting critical information, such as patient-reported outcomes (PROs), to be shared at points of care and in between appointments. We describe the implementation strategies and outcomes of a multistakeholder collaborative process known as "co-design" to develop a PRO-informed clinical dashboard to support SDM for patients with advanced cancer or chronic kidney disease (CKD). Methods: Across 14 sessions, two multidisciplinary teams comprising patients, care partners, clinicians, and other stakeholders iteratively co-designed an SDM dashboard for either advanced cancer (N = 25) or CKD (N = 24). Eligible patients, care partners, and frontline clinicians were identified by six physician champions. The co-design process included four key steps: (1) define "the problem", (2) establish context of use, (3) build a consensus on design, and (4) define and test specifications. We also evaluated our success in implementing the co-design strategy using measures of fidelity, acceptability, adoption, feasibility, and effectiveness which were collected throughout the process. Results: Mean (M) scores across implementation measures of the co-design process were high, including observer-rated fidelity and adoption of co-design practices (M = 19.1 on a 7-21 scale, N = 36 ratings across 9 sessions), as well as acceptability based on the perceived degree of SDM that occurred during the co-design process (M = 10.4 on a 0 to 12 adapted collaboRATE scale). Capturing the feasibility and adoption of convening multistakeholder co-design teams, min-max normalized scores (ranging from 0 to 1) of stakeholder representation demonstrated that, on average, 95% of stakeholder types were represented for cancer sessions (M = 0.95) and 85% for CKD sessions (M = 0.85). The co-design process was rated as either "fully" or "partially" effective by 100% of respondents, in creating a dashboard that met its intended objective. Conclusions: A co-design process was successfully implemented to develop SDM clinical dashboards for advanced cancer and CKD care. We discuss key strategies and learnings from this process that may aid others in the development and uptake of patient-centered healthcare innovations.

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Medicare is the largest single purchaser of health care in the United States and currently helps to pay medical expenses for approximately one-fifth of the US population. The impetus for Medicare to move away from fee-for-service and toward value-based care payments reflects the need to incentivize and improve healthcare quality while containing increasing costs. This primer provides a detailed overview of several interrelated topics for an improved understanding of the Medicare program for orthopaedic surgeons, other clinicians, healthcare administrators, policymakers, and business leaders. An improved understanding may stimulate additional ideas for successful program advancements.

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PURPOSE: Telemedicine provides numerous benefits to patients, yet effective communication and symptom assessment remain a concern. The recent uptake of telemedicine provided an opportunity to use a newly developed dashboard with patient-reported outcome (PRO) information to enhance communication and shared decision making (SDM) during telemedicine appointments. The objective of this study was to identify barriers to using the dashboard during telemedicine, develop implementation strategies to address barriers, and pilot test use of this dashboard during telemedicine appointments in two practice settings to evaluate acceptability, adoption, fidelity, and effectiveness. METHODS: Patients and clinicians were interviewed to identify determinants to dashboard use in telemedicine. Implementation strategies were designed and refined through iterative feedback from stakeholders. A pilot study of dashboard use was conducted from March to September 2022. Acceptability, adoption, and fidelity were evaluated using mixed methods. SDM was evaluated using the collaboRATE measure. RESULTS: One hundred two patient encounters were evaluated. Most patients (62; 60%) had completed some PRO data at the time of their telemedicine encounter. Most (82; 80%) encounters had clinician confirmation that PRO data had been reviewed; however, collaborative review of the dashboard was documented in only 27%. Degree of SDM was high (mean collaboRATE score 3.40; SD, 0.11 [95% CI, 3.17 to 3.63] out of a maximum score of 4). Implementation strategies focused on patient engagement, education, and remote PRO completion. Clinician-facing strategies included education, practice facilitation, and small tests of change. CONCLUSION: This study demonstrated that implementation of a PRO-based dashboard into telemedicine appointments was feasible and had acceptable adoption and acceptability by patients and clinicians when several strategies were used to engage end users. Strategies targeting both patients and clinicians are needed to support routine and effective PRO integration in telemedicine.

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BACKGROUND: Patient-reported outcome (PRO) measures have become an essential component of quality measurement, quality improvement, and capturing the voice of the patient in clinical care. In 2004, the National Institutes of Health endorsed the importance of PROs by initiating the Patient-Reported Outcomes Measurement Information System (PROMIS), which leverages computer-adaptive tests (CATs) to reduce patient burden while maintaining measurement precision. Historically, PROMIS CATs have been used in a large number of research studies outside the electronic health record (EHR), but growing demand for clinical use of PROs requires creative information technology solutions for integration into the EHR. OBJECTIVES: This paper describes the introduction of PROMIS CATs into the Epic Systems EHR at a large academic medical center using a tight integration; we describe the process of creating a secure, automatic connection between the application programming interface (API) which scores and selects CAT items and Epic. METHODS: The overarching strategy was to make CATs appear indistinguishable from conventional measures to clinical users, patients, and the EHR software itself. We implemented CATs in Epic without compromising patient data security by creating custom middleware software within the organization's existing middleware framework. This software communicated between the Assessment Center API for item selection and scoring and Epic for item presentation and results. The middleware software seamlessly administered CATs alongside fixed-length, conventional PROs while maintaining the display characteristics and functions of other Epic measures, including automatic display of PROMIS scores in the patient's chart. Pilot implementation revealed differing workflows for clinicians using the software. RESULTS: The middleware software was adopted in 27 clinics across the hospital system. In the first 2 years of hospital-wide implementation, 793 providers collected 70,446 PROs from patients using this system. CONCLUSION: This project demonstrated the importance of regular communication across interdisciplinary teams in the design and development of clinical software. It also demonstrated that implementation relies on buy-in from clinical partners as they integrate new tools into their existing clinical workflow.

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Purpose: Sexual orientation, gender identity, and sex recorded at birth (SOGI) have been routinely excluded from demographic data collection tools, including in electronic medical record (EMR) systems. We assessed the ability of adding structured SOGI data capture to improve identification of transgender and nonbinary (TGNB) patients compared to using only International Classification of Diseases (ICD) codes and text mining and comment on the ethics of these cohort formation methods. Methods: We conducted a retrospective chart review to classify patient gender at a single institution using ICD-10 codes, structured SOGI data, and text mining for patients presenting for care between March 2019 and February 2021. We report each method's overall and segmental positive predictive value (PPV). Results: We queried 1,530,154 EMRs from our institution. Overall, 154,712 contained relevant ICD-10 diagnosis codes, SOGI data fields, or text mining terms; 2964 were manually reviewed. This multipronged approach identified a final 1685 TGNB patient cohort. The initial PPV was 56.8%, with ICD-10 codes, SOGI data, and text mining having PPV of 99.2%, 47.9%, and 62.2%, respectively. Conclusion: This is one of the first studies to use a combination of structured data capture with keyword terms and ICD codes to identify TGNB patients. Our approach revealed that although structured SOGI documentation was <10% in our health system, 1343/1685 (79.7%) of TGNB patients were identified using this method. We recommend that health systems promote patient EMR documentation of SOGI to improve health and wellness among TGNB populations, while centering patient privacy.

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PURPOSE: Cancer staging is the foundation for all cancer management decisions. For real-time use, stage must be embedded in the electronic health record as a discrete data element. The objectives of this quality improvement (QI) initiative were to (1) identify barriers to utilization of an existing discrete cancer staging module, (2) identify health information technology (HIT) solutions to support discrete capture of cancer staging data, and (3) increase capture across the oncology enterprise in our diverse health system. METHODS: Six sigma QI methodologies were used to define barriers and solutions to improve discrete cancer staging. Design thinking principles informed solution development to test prototypes. Two multidisciplinary teams of disease-specific clinicians within GI and genitourinary conducted phased testing pilots to determine health system solutions. Solutions were expanded to all oncology specialties across our health system. RESULTS: Baseline average discrete staging capture across our health system was 31%. Poor workflow efficiency, limited accountability, and technical design gaps were key barriers to timely, complete staging. Implementation of more than 25 design enhancements to a HIT solution and passive user alerts led to a postimplementation capture rate of 58% across 55 outpatient clinics involving more than 400 clinicians. CONCLUSION: We identified key barriers to discrete data capture and designed solutions through iterative use of QI methodologies and disease-specific pilots. After implementation, discrete capture of cancer staging nearly doubled across our diverse health system. This approach is scalable and transferable to other initiatives to develop and implement clinically relevant HIT solutions across a diverse health system.

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The number of publicly available hospital quality rating systems has substantially increased over the past 2 decades. These rating systems are meant to provide patients, clinicians, and payers with relevant information to select and pay differentially for better quality of care. However, there is evidence of inconsistency, unreliability, and bias in current hospital quality rating systems. Financial ratings are similarly intended to enable investors to identify stronger companies (as investment targets), and these rating systems could provide insight into strategies to improve hospital quality ratings. We evaluate the credit rating methodologies of Standard & Poor's, Moody's, and Fitch Group and propose principles to improve hospital quality rating systems through better standardized measures and the use of external audits of source data. Emulating key features of credit rating systems may advance the delivery of meaningful hospital quality ratings.

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BACKGROUND: Patient-reported outcomes-symptoms, treatment side effects, and health-related quality of life-are important to consider in chronic illness care. The increasing availability of health IT to collect patient-reported outcomes and integrate results within the electronic health record provides an unprecedented opportunity to support patients' symptom monitoring, shared decision-making, and effective use of the health care system. OBJECTIVE: The objectives of this study are to co-design a dashboard that displays patient-reported outcomes along with other clinical data (eg, laboratory tests, medications, and appointments) within an electronic health record and conduct a longitudinal demonstration trial to evaluate whether the dashboard is associated with improved shared decision-making and disease management outcomes. METHODS: Co-design teams comprising study investigators, patients with advanced cancer or chronic kidney disease, their care partners, and their clinicians will collaborate to develop the dashboard. Investigators will work with clinic staff to implement the co-designed dashboard for clinical testing during a demonstration trial. The primary outcome of the demonstration trial is whether the quality of shared decision-making increases from baseline to the 3-month follow-up. Secondary outcomes include longitudinal changes in satisfaction with care, self-efficacy in managing treatments and symptoms, health-related quality of life, and use of costly and potentially avoidable health care services. Implementation outcomes (ie, fidelity, appropriateness, acceptability, feasibility, reach, adoption, and sustainability) during the co-design process and demonstration trial will also be collected and summarized. RESULTS: The dashboard co-design process was completed in May 2020, and data collection for the demonstration trial is anticipated to be completed by the end of July 2022. The results will be disseminated in at least one manuscript per study objective. CONCLUSIONS: This protocol combines stakeholder engagement, health care coproduction frameworks, and health IT to develop a clinically feasible model of person-centered care delivery. The results will inform our current understanding of how best to integrate patient-reported outcome measures into clinical workflows to improve outcomes and reduce the burden of chronic disease on patients and health care systems. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/38461.

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BACKGROUND: Culture of safety (COS) is recognized as a critical component of patient safety but can be burdensome to measure due to survey length. This project aimed to develop a shortened COS survey with comparable measurement properties to a validated 19-item instrument. METHODS: Item response theory (IRT) was used to reduce items from a 19-item COS survey at a 10-hospital health system. Using a 50% random sample, IRT was applied to evaluate survey question discrimination and information. Concepts from the key questions in each subdomain were reworded into a new abbreviated scale. Cognitive interviews with clinicians were conducted to validate reworded questions for adequacy, clarity, and consistency of interpretation. RESULTS: The 19-item survey was reduced with IRT to 4 items. Cronbach's alpha for the 4-item IRT-derived scale was 0.80 (average inter-item covariance = 0.36) and was comparable to the original scale despite ∼75% reduction in items. Pearson correlation between the 4-item scale and the original scale was > 0.90. The 4-item scale demonstrated convergent validity. Results were replicated in a 50% random validation sample. Cognitive interviews revealed inadequacy of the shortened scale in assessing error-reporting culture. A fifth item was developed and qualitatively validated for this construct. CONCLUSION: Using a mixed methods approach, a lengthy COS survey was condensed and revised to a brief 5-question survey with comparable measurement properties and respondent interpretation. A shorter instrument necessarily loses detailed insight into multiple aspects of safety culture, and organizations should consider trade-offs in choosing to develop a briefer survey.

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BACKGROUND: Prior studies have reported decreases in the preterm delivery incidence during the COVID-19 pandemic. However, the findings are inconsistent. Given the wide disparities in the pandemic's impact across communities, neighborhood deprivation may explain the observed variation in the relationship between the COVID-19 pandemic and preterm delivery. OBJECTIVE: To characterize the changes in the incidence of preterm delivery during the COVID-19 pandemic with attention to the effect modification introduced by neighborhood hardship. STUDY DESIGN: This retrospective cohort study included all the pregnant patients who delivered at an urban tertiary care hospital during the pandemic (April-November 2020) or before the pandemic (April-November 2019). We compared the incidence of preterm delivery, spontaneous preterm delivery, and medically indicated preterm delivery before 37 weeks' gestation across epochs. Planned analyses stratified the cohorts by neighborhood deprivation metrics defined by the residential zip code; the metrics included the median neighborhood household income and the hardship index (a composite index including dependency, educational attainment, unemployment, poverty, per capita income, and crowded housing). The Breslow-Day test for homogeneity assessed the association of the delivery epoch and neighborhood deprivation with the preterm delivery outcomes. RESULTS: Of 16,544 eligible deliveries, 8.7% occurred preterm. The incidences of preterm delivery (8.4% vs 9.0%; P=.17), spontaneous preterm delivery (5.0 vs 5.4%; P=.27), and medically indicated preterm delivery (3.2% vs 3.5%; P=.47) were similar in the pandemic and prepandemic epochs. However, the preterm delivery (odds ratio, 0.78; 95% confidence interval, 0.64-0.96) and spontaneous preterm delivery (odds ratio, 0.76; 95% confidence interval, 0.59-0.99) decreased from the prepandemic to the pandemic epoch in those living in neighborhoods <50th percentile for median income (Breslow-Day P values.047 and.036, respectively). Similarly, the preterm delivery (odds ratio, 0.78; 95% confidence interval, 0.64-0.97) and spontaneous preterm delivery (odds ratio, 0.74; 95% confidence interval, 0.57-0.98) decreased for those inhabiting the neighborhoods in the highest-hardship quartile (Breslow-Day P values.045 and.029, respectively). CONCLUSION: The populations residing in socioeconomically disadvantaged neighborhoods experienced reductions in preterm delivery during the COVID-19 pandemic. Neighborhood-level social determinants of health offer insight into the complex etiologies that contribute to preterm delivery and provide opportunities for public health and equity-focused prevention strategies.

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Importance: Certificate of need laws provide state-level regulation of health system expenditure. These laws are intended to limit spending and control hospital expansion in order to prevent excess capacity and improve quality of care. Several states have recently introduced legislation to modify or repeal these regulations, as encouraged by executive order 13813, issued in October 2017 by the Trump administration. Objective: To evaluate the difference in markers of hospital activity and quality by state certificate of need status. These markers include hospital procedural volume, hospital market share, county-level procedures per 10 000 persons, and patient-level postoperative outcomes. Design, Setting, and Participants: A cross-sectional study involving Medicare beneficiaries aged 65 years or older who underwent 1 of the following 10 procedures from January 1, 2016, through November 30, 2018: total knee or hip arthroplasty, coronary artery bypass grafting, colectomy, ventral hernia repair, lower extremity vascular bypass, lung resection, pancreatic resection, cystectomy, or esophagectomy. Exposures: State certificate of need regulation status as determined by data from the National Conference of State Legislatures. Main Outcomes and Measures: Outcomes of interest included hospital procedural volume; hospital market share (range, 0-1; reflecting 0%-100% of market share); county-level procedures per 10 000 persons; and patient-level postoperative 30-day mortality, surgical site infection, and readmission. Results: A total of 1 545 952 patients (58.0% women; median age 72 years; interquartile range, 68-77 years) at 3631 hospitals underwent 1 of the 10 operations. Of these patients, 468 236 (30.3%) underwent procedures in the 15 states without certificate of need regulations and 1 077 716 (69.7%) in the 35 states with certificate of need regulations. The total number of procedures ranged between 729 855 total knee arthroplasties (47.21%) and 4558 esophagectomies (0.29%). When comparing states without vs with certificate of need regulations, there were no significant differences in overall hospital procedural volume (median hospital procedure volume, 241 vs 272 operations per hospital for 3 years; absolute difference, 31; 95% CI, -27.64 to 89.64; P = .30). There were no statistically significant differences between states without vs with certificate of need regulations for median hospital market share (median, 28% vs 52%; absolute difference, 24%; 95% CI, -5% to 55%; P = .11); procedure rates per 10 000 Medicare-eligible population (median, 239.23 vs 205.41 operations per Medicare-eligible population in 3 years; absolute difference, 33.82; 95% CI, -84.08 to 16.43; P = .19); or 30-day mortality (1.17% vs 1.33%, odds ratio [OR], 1.04; 95% CI, 0.93 to 1.16; P = .52), surgical site infection (1.24% vs 1.25%; OR, 0.93; 95% CI, 0.83 to 1.04; P = .21), or readmission rate (9.69% vs 8.40%; OR, 0.80; 95% CI, 0.57 to 1.12; P = .19). Conclusions and Relevance: Among Medicare beneficiaries who underwent a range of surgical procedures from 2016 through 2018, there were no significant differences in markers of hospital volume or quality between states without vs with certificate of need laws. Policy makers should consider reevaluating whether the current approach to certificate of need regulation is achieving the intended objectives and whether those objectives should be updated.

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BACKGROUND: Unmanaged cancer symptoms and treatment-related side effects can compromise long-term clinical outcomes and health-related quality of life. Health information technologies such as web-based platforms offer the possibility to supplement existing care and optimize symptom management. OBJECTIVE: This paper describes the development and usability of a web-based symptom management platform for cancer patients and survivors that will be implemented within a large health system. METHODS: A web-based symptom management platform was designed and evaluated via one-on-one usability testing sessions. The System Usability Scale (SUS), After Scenario Questionnaire (ASQ), and qualitative analysis of semistructured interviews were used to assess program usability. RESULTS: Ten cancer survivors and five cancer center staff members participated in usability testing sessions. The mean score on the SUS was 86.6 (SD 14.0), indicating above average usability. The mean score on the ASQ was 2.5 (SD 2.1), indicating relatively high satisfaction with the usability of the program. Qualitative analyses identified valued features of the program and recommendations for further improvements. CONCLUSIONS: Cancer survivors and oncology care providers reported high levels of acceptability and usability in the initial development of a web-based symptom management platform for cancer survivors. Future work will test the effectiveness of this web-based platform.

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BACKGROUND: The cost of surgical care is largely measured by charges or payments, both of which are inadequate. Actual cost data from the hospital's perspective are required to accurately quantify the financial return on investment of engaging in quality improvement. The objective of this study was to define the cost of individual, 30-day postoperative complications using robust cost data from a diverse group of hospitals. METHODS: Using clinical data derived from the American College of Surgeons National Surgical Quality Improvement Program, this retrospective study assessed postoperative complications for patients who underwent surgery at one of four hospitals in 2016. Actual direct and indirect 30-day costs were obtained, and the adjusted cost per complication was determined. RESULTS: From the 6,387 patients identified, the three complications associated with the highest independent adjusted cost per event were prolonged ventilation ($48,168; 95% confidence interval [CI]: $21,861-$74,476), unplanned intubation ($26,718; 95% CI: $15,374-$38,062), and renal failure ($18,528; CI: $17,076-$19,981). The three complications associated with the lowest independent adjusted cost per event were urinary tract infection (-$372; 95% CI: -$1,336-$592), superficial surgical site infection ($2,473; 95% CI: -$256-$5,201) and venous thromboembolism ($7,909; 95% CI: -$17,903-$33,721). After colectomy, the adjusted independent cost of anastomotic leak was $10,195 (95% CI: $5,941-$14,449), while the cost of postoperative ileus was $10,205 (95% CI: $6,259-$14,149). CONCLUSION: The actual hospital costs of complications were estimated using cost data from four diverse hospitals. These data can be used by hospitals to estimate the financial benefit of reducing surgical complications.

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INTRODUCTION: Despite widely appreciated barriers to successful clinical implementation, the literature regarding how to operationalize electronic health record-integrated patient-reported outcomes (PROs) remains sparse. We offer a detailed summary of the implementation of PROs into the standard of care at a major tertiary academic medical center. METHODS: Collection of four Patient-Reported Outcomes Measurement Information System computer adaptive tests was piloted in a large academic orthopaedic surgery ambulatory clinic starting in October 2016. The Patient-Reported Outcomes Measurement Information System computer adaptive tests (Physical Function, Pain Intensity, Pain Interference, and Ability to Return to Social Roles and Activities) were initially implemented as manual order sets to be administered before surgery through 2 years after surgery. Completion rate over time, mean time to completion for all PRO domains, and the overall distribution of symptom severity were used to evaluate the success of the pilot. A subsequent optimization and redesign of the pilot was conducted using tablets, automation of questionnaire deployment, and improved results review to address obstacles encountered during the pilot phase. RESULTS: Two thousand nine distinct joint arthroplasty patients (mean age = 65) completed at least one set of PRO assessments, with overall completion rates reaching 68% and mean completion time of 3 minutes. Focal points during the implementation process included engagement and training of staff, selection of an appropriate patient population and outcome measures, and user friendly data displays for patients and providers. CONCLUSION: Our pilot program successfully demonstrated that PROs can be administered, scored, and made immediately available within the electronic health record to patients and their providers with minimal disruption of clinical workflows. Although considerable operational and technological challenges remain, we found that the implementation of PROs in clinical care within an ambulatory practice at an academic medical center can be achieved through a constellation of several key factors.

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The star rating system for hospitals of the Centers for Medicare and Medicaid Services (CMS) pools all hospitals together and awards each institution one to five stars for quality, despite variation across hospitals in the numbers and types of measures they report. Thus, hospitals essentially are being evaluated differently, which affects the validity of quality comparisons. We considered the number and types of measures reported and the size of measure denominators to represent different forms of a "test," and we used data from the December 2017 star ratings to show that hospitals took one of three general "test forms." Hospitals taking the most extensive test form reported an average of forty-three measures, while those taking the least extensive test reported an average of twenty-two measures. These test forms were differentially associated with star ratings and hospital characteristics. Our results caution against pooling all hospitals together when assigning star ratings, and they demonstrate a feasible approach to segmenting hospitals into peer groups for evaluation by stakeholders such as CMS.

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