Predicting Unplanned Health Care Utilization and Cost: Comparing Patient-reported Outcomes Measurement Information System and Claims.

OBJECTIVES: There is little literature describing if and how payers are utilizing patient-reported outcomes to predict future costs. This study assessed if Patient-reported Outcomes Measurement Information System (PROMIS) domain scores, collected in routine practice at neurology clinics, improved payer predictive models for unplanned care utilization and cost. STUDY DESIGN: Retrospective cohort analysis of private Health Plan-insured patients with visits at 18 Health Plan-affiliated neurology clinics. METHODS: PROMIS domains (Anxiety v1.0, Cognitive Function Abilities v2.0, Depression v1.0, Fatigue v1.0, Pain Interference v1.0, Physical Function v2.0, Sleep Disturbance v1.0, and Ability to Participate in Social Roles and Activities v2.0) are collected as part of routine care. Data from patients' first PROMIS measures between June 27, 2018 and April 16, 2019 were extracted and combined with claims data. Using (1) claims data alone and (2) PROMIS and claims data, we examined the association of covariates to utilization (using a logit model) and cost (using a generalized linear model). We evaluated model fit using area under the receiver operating characteristic curve (for unplanned care utilization), akaike information criterion (for unplanned care costs), and sensitivity and specificity in predicting top 15% of unplanned care costs. RESULTS: Area under the receiver operating curve values were slightly higher, and akaike information criterion values were similar, for PROMIS plus claims covariates compared with claims alone. The PROMIS plus claims model had slightly higher sensitivity and equivalent specificity compared with claims-only models. CONCLUSION: One-time PROMIS measure data combined with claims data slightly improved predictive model performance compared with claims alone, but likely not to an extent that indicates improved practical utility for payers.

Perceived performance and impact of a non-physician-led interprofessional team in a trauma clinic setting.

Faced with the challenge of meeting the wide degree of post-discharge needs in their trauma population, the University of Pittsburgh Medical Center (UPMC) developed a non-physician-led interprofessional team to provide follow-up care at its UPMC Falk Trauma Clinic. We assessed this model of care using a survey to gauge team member perceptions of this model, and used clinic visit documentation to apply a novel approach to assessing how this model improves the care received by clinic patients. The high level of perceived team performance and cohesion suggests that this model has been successful thus far from a provider perspective. Patients are seen most frequently by audiologists, while approximately half of physical therapy and speech language therapy consults generate a new therapy referral, which is interpreted as a potential change in the patient's care trajectory. The broader message of this analysis is that a collaborative, non-hierarchical team model incorporating rehabilitative specialists, who often operate independently of one another, can be successful in this setting, where patients appear to have a strong and previously under-attended need for rehabilitative intervention.

New chronic disease medication prescribing by nurse practitioners, physician assistants, and primary care physicians: a cohort study.

BACKGROUND: Medications to treat and prevent chronic disease have substantially reduced morbidity and mortality; however, their diffusion has been uneven. Little is known about prescribing of chronic disease medications by nurse practitioners (NPs) and physician assistants (PAs), despite their increasingly important role as primary care providers. Thus, we sought to conduct an exploratory analysis to examine prescribing of new chronic disease medications by NPs and PAs compared to primary care physicians (PCPs). METHODS: We obtained prescribing data from IMS Health's Xponent™ on all NPs, PAs, and PCPs in Pennsylvania regularly prescribing anticoagulants, antihypertensives, oral hypoglycemics, and/or HMG-Co-A reductase inhibitors pre- and post-introduction of five new drugs in these classes that varied in novelty (i.e., dabigatran, aliskiren, sitagliptin or saxagliptin, and pitavastatin). We constructed three measures of prescriber adoption during the 15-month post-FDA approval period: 1) any prescription of the medication, 2) proportion of prescriptions in the class for the medication, and 3) time to adoption (first prescription) of the medication. RESULTS: From 2007 to 2011, the proportion of antihypertensive prescriptions prescribed by NPs and PAs approximately doubled from 2.0 to 4.2 % and 2.2 to 4.9 %, respectively. Similar trends were found for anticoagulants, oral hypoglycemics, and HMG-Co-A reductase inhibitors. By 2011, more PCPs had prescribed each of the newly approved medications than NPs and PAs (e.g., 44.3 % vs. 18.5 % vs. 20 % for dabigatran among PCPs, NPs, and PAs). Across all medication classes, the newly approved drugs accounted for a larger share of prescriptions in the class for PCPs followed by PAs, followed by NPs (e.g., dabigatran: 4.9 % vs. 3.2 % vs. 2.8 %, respectively). Mean time-to-adoption for the newly approved medications was shorter for PCPs compared to NPs and PAs (e.g., dabigatran, 7.3 vs. 8.2 vs. 8.5 months; P all medications <0.001). CONCLUSIONS: PCPs were more likely to prescribe each of the newly approved medications per each measure of drug adoption, regardless of drug novelty. Differences in the rate and speed of drug adoption between PCPs, NPs, and PAs may have important implications for care and overall costs at the population level as NPs and PAs continue taking on a larger role in prescribing.

Comparing Advanced Practice Providers and Physicians as Providers of e-Visits.

BACKGROUND: Although electronic delivery (electronic visits [e-visits]) of healthcare services by advanced practice providers (APPs) is growing, literature defining the roles of different providers and comparing outcomes is lacking. We analyzed two e-visit models at the University of Pittsburgh Medical Center (UPMC) to compare their providers (physicians and APPs) and associated outcomes. MATERIALS AND METHODS: We identified all e-visits for the UPMC AnywhereCare Continuity (physician providers for existing patients) and Convenience (physician and APP providers for Pennsylvania residents) services (n=2,184) using Epic Systems (Verona, WI) MyChart data (November 2013-August 2014). We compared e-visits by service and provider type for patient characteristics, volume, response time, primary diagnoses, and number of prescriptions. We used statistical tests to determine differences in patient characteristics and an ordinary least square linear regression, controlling for patient characteristics, to determine differences in prescribing. RESULTS: Of the completed e-visits (n=1,791), 72.5% were with APPs, and 27.5% were with physicians. APP patients were younger, higher income, and more likely to be unmarried. Sinusitis patients were more likely to use the Continuity service, whereas those with urinary tract or upper respiratory infections were more likely to use the Convenience service. Finally, provider type was significantly associated with prescribing, with APPs prescribing more. CONCLUSIONS: Some demographic variation exists between users of APP versus physician e-visits. Provider response time seems more driven by service policy than provider type. Finally, variation exists between provider types in quantities of prescriptions written. As health systems and policymakers develop protocols and reimbursement strategies for e-visits, these model considerations will be important.

Innovative approaches to interprofessional care at the University of Pittsburgh Medical Center.

The enactment of the Affordable Care Act expands coverage to millions of uninsured Americans and creates a new workforce landscape. Interprofessional Collaborative Practice (ICP) is no longer a choice but a necessity. In this paper, we describe four innovative approaches to interprofessional practice at the University of Pittsburgh Medical Center. These models demonstrate innovative applications of ICP to inpatient and outpatient care, relying on non-physician providers, training programs, and technology to deliver more appropriate care to specific patient groups. We also discuss the ongoing evaluation plans to assess the effects of these interprofessional practices on patient health, quality of care, and healthcare costs. We conclude that successful implementation of interprofessional teams involves more than just a reassignment of tasks, but also depends on structuring the environment and workflow in a way that facilitates team-based care.

Association of Outpatient Behavioral Health Treatment With Medical and Pharmacy Costs in the First 27 Months Following a New Behavioral Health Diagnosis in the US.

Importance: Outpatient behavioral health treatment (OPBHT) is an effective treatment for behavioral health conditions (BHCs) that may also be associated with improved medical health outcomes, but evidence regarding the cost-effectiveness of OPBHT across a large population has not been established. Objective: To investigate whether individuals newly diagnosed with a BHC who used OPBHT incurred lower medical and pharmacy costs over 15 and 27 months of follow-up compared with those not using OPBHT. Design, Setting, and Participants: This retrospective cohort study of commercially insured individuals in the US was conducted using administrative insurance claims data for individuals newly diagnosed with 1 or more BHCs between January 1, 2017, and December 31, 2018. Data were examined using a 12-month period before BHC diagnosis and 15- and 27-month follow-up periods. Participants included individuals aged 1 to 64 years who received any OPBHT with or without behavioral medication or who did not receive OPBHT or behavioral medication in the 15 months following diagnosis. Data were analyzed from May to October 2021. Exposures: Receipt of OPBHT both as a dichotomous variable and categorized by number of OPBHT visits. Main Outcomes and Measures: The main outcome was the association between OPBHT treatment and 15- and 27-month medical and pharmacy costs, assessed using a generalized linear regression model with γ distribution, controlling for potential confounders. Results: The study population included 203 401 individuals, of whom most were male (52%), White, non-Hispanic (75%), and 18 to 64 years of age (67%); 22% had at least 1 chronic medical condition in addition to a BHC. Having 1 or more OPBHT visits was associated with lower adjusted mean per-member, per-month medical and pharmacy costs across follow-up over 15 months (no OPBHT: $686 [95% CI, $619-$760]; ≥1 OPBHT: $571 [95% CI, $515-$632]; P < .001) and 27 months (no OPBHT: $464 [95% CI, $393-$549]; ≥1 OPBHT: $391 [95% CI, $331-$462]; P < .001). Furthermore, almost all doses of OPBHT across the 15 months following diagnosis were associated with lower costs compared with no OPBHT. Conclusions and Relevance: In this cohort study, medical cost savings were associated with OPBHT among patients newly diagnosed with a BHC in a large, commercially insured population. The findings suggest that promoting and optimizing OPBHT may be associated with reduced overall medical spending among patients with BHCs.

Associations between Reason for Inpatient Palliative Care Consultation, Timing, and Cost Savings.

Background: Specialty palliative care (SPC) provides patient-centered care to people with serious illness and may reduce costs. Specific cost-saving functions of SPC remain unclear. Objectives: (1) To assess the effect of SPC on inpatient costs and length of stay (LOS) and (2) to evaluate differences in costs by indication and timing of SPC. Design: Case-control with in patients who received an SPC consultation and propensity matched controls. Setting: One large U.S. integrated delivery finance system. Measurements: Using administrative data, we assessed costs associated with inpatient stays, a subset of whom received an SPC consultation. Consultations were stratified by reasons based on physician discretion: goals of care, pain management, hospice evaluation, nonpain symptom management, or support. The primary outcome was total operating costs and the secondary outcome was hospital LOS. Results: In total, 1404 patients with SPC consultations associated with unique hospital encounters were matched with 2806 controls. Total operating costs were lower for patients who received an SPC consultation when the consultation was within 0 to 1 days of admission ($6,924 vs. $7,635, p = 0.002). Likewise, LOS was shorter (4.3 vs. 4.7 days, p < 0.001). Upon stratification by reason, goals-of-care consultations early in the hospital stay (days 0-1) were associated with reduced total operating costs ($7,205 vs. $8,677, p < 0.001). Costs were higher for pain management consultations ($7,727 vs. $6,914, p = 0.047). Consultation for hospice evaluation was associated with lower costs, particularly when early (hospital days 0-1: $4,125 vs. $7,415, p < 0.001). Conclusions: SPC was associated with significant cost saving and decreased LOS when occurring early in a hospitalization and used for goals-of-care and hospice evaluation.

Development of a Novel Pancreatoduodenectomy-Specific Risk Calculator: an Analysis of 10,000 Patients.

BACKGROUND: Pancreatoduodenectomy (PD) is often performed in frail patients and is associated with significant morbidity. The five-factor modified frailty index (mFI-5) has been utilized to predict adverse postoperative outcomes, but has not been tested in PD. We aimed to develop risk tools to generate and predict 30-day outcomes after PD and compare their performance with the mFI-5. Risk tools were then used to generate a PD-specific calculator. METHODS: Elective PDs from the 2014-2016 ACS NSQIP® Procedure Targeted Pancreatectomy PUFs were identified. Multivariable logistic regression models were constructed to predict postoperative mortality, any complication, serious complication, clinically relevant postoperative pancreatic fistula (CR-POPF), and discharge not-to-home. Predictive accuracy was evaluated through repeated stratified tenfold cross-validation and compared to the mFI-5. RESULTS: Nine thousand eight hundred sixty-seven PDs were captured. Nine risk factors were retained: sex, age, BMI, DM, HTN, ASA classification, pancreatic duct size, gland texture, and adenocarcinoma. Cross-validated C-indices ranged from 0.49 to 0.61 for the mFI-5 and 0.63 to 0.75 for our risk models. The best-performing model was for discharge not-to-home (C = 0.75), and the model delivering the largest increase in predictive accuracy was for CR-POPF (CmFI-5/Model = 0.49/0.70). A user-friendly risk calculator was created predicting the five outcomes of interest. CONCLUSION: We have created a PD-specific risk calculator that outperforms the mFI-5. This calculator may serve as a useful adjunct in shared decision-making for patients and surgeons.

Remote monitoring for heart failure: Assessing the risks of readmission and mortality.

Study objective: Remote monitoring (RM) can help patients with heart failure (HF) remain free of hospitalization. Our objective was to implement a patient-centered RM program that ensured timely clinical response, which would be associated with reduced mortality. Design: This was a retrospective, observational, propensity-matched study. Setting: A large regional health system between 9/1/2016-1/31/2018. Participants: Patients admitted with acute HF exacerbation were matched on key variables. Up to two comparison patients were selected for each RM user. Interventions: We used an algorithmic approach to assess daily physiologic data, assess symptoms, provide patient education, encourage patient self-management, and triage medical problems. Main outcome measures: We assessed all-cause mortality using Kaplan-Meier and log rank analysis. We used Cox proportional hazards to compare risk of death. Results: Our cohort of 680 RM users and 1198 comparisons were similar across baseline characteristics except age (74.7 years versus 76.6 years, p < 0.001, respectively). Having one or more admissions in the preceding 120 days was more prevalent in the RM group (35.9% versus 29.8%, p = 0.013). The 30- and 90-day all-cause readmission rates were each higher among the RM users compared with the comparison patients (p = 0.013 and p < 0.001 for 30 and 90 days, respectively). Mortality was lower in the RM group at 30 and 90 days post-discharge (p < 0.001). Conclusions: RM that responds to biometric data and encourages patient self-management can be used in a large hospital system and is associated with decreased all-cause mortality. Our findings underscore RM technology as a method to improve HF care.

SafeNET: Initial development and validation of a real-time tool for predicting mortality risk at the time of hospital transfer to a higher level of care.

BACKGROUND: Processes for transferring patients to higher acuity facilities lack a standardized approach to prognostication, increasing the risk for low value care that imposes significant burdens on patients and their families with unclear benefits. We sought to develop a rapid and feasible tool for predicting mortality using variables readily available at the time of hospital transfer. METHODS AND FINDINGS: All work was carried out at a single, large, multi-hospital integrated healthcare system. We used a retrospective cohort for model development consisting of patients aged 18 years or older transferred into the healthcare system from another hospital, hospice, skilled nursing or other healthcare facility with an admission priority of direct emergency admit. The cohort was randomly divided into training and test sets to develop first a 54-variable, and then a 14-variable gradient boosting model to predict the primary outcome of all cause in-hospital mortality. Secondary outcomes included 30-day and 90-day mortality and transition to comfort measures only or hospice care. For model validation, we used a prospective cohort consisting of all patients transferred to a single, tertiary care hospital from one of the 3 referring hospitals, excluding patients transferred for myocardial infarction or maternal labor and delivery. Prospective validation was performed by using a web-based tool to calculate the risk of mortality at the time of transfer. Observed outcomes were compared to predicted outcomes to assess model performance. The development cohort included 20,985 patients with 1,937 (9.2%) in-hospital mortalities, 2,884 (13.7%) 30-day mortalities, and 3,899 (18.6%) 90-day mortalities. The 14-variable gradient boosting model effectively predicted in-hospital, 30-day and 90-day mortality (c = 0.903 [95% CI:0.891-0.916]), c = 0.877 [95% CI:0.864-0.890]), and c = 0.869 [95% CI:0.857-0.881], respectively). The tool was proven feasible and valid for bedside implementation in a prospective cohort of 679 sequentially transferred patients for whom the bedside nurse calculated a SafeNET score at the time of transfer, taking only 4-5 minutes per patient with discrimination consistent with the development sample for in-hospital, 30-day and 90-day mortality (c = 0.836 [95%CI: 0.751-0.921], 0.815 [95% CI: 0.730-0.900], and 0.794 [95% CI: 0.725-0.864], respectively). CONCLUSIONS: The SafeNET algorithm is feasible and valid for real-time, bedside mortality risk prediction at the time of hospital transfer. Work is ongoing to build pathways triggered by this score that direct needed resources to the patients at greatest risk of poor outcomes.

Does Preoperative MELD Score Predict Adverse Outcomes Following Pancreatic Resection: an ACS NSQIP Analysis.

BACKGROUND: Higher MELD scores correlate with adverse operative outcomes regardless of the presence of liver disease, but their impact on pancreatectomy outcomes remains undefined. We aimed to compare 30-day adverse postoperative outcomes of patients undergoing elective pancreatectomy stratified by MELD score. METHODS: Elective pancreatoduodenectomies (PDs) and distal pancreatectomies (DPs) were identified from the 2014-2016 ACS NSQIP Procedure Targeted Pancreatectomy Participant Use Data Files. Outcomes examined included mortality, cardiopulmonary complications, prolonged postoperative length-of-stay, discharge not-to-home, transfusion, POPF, CR-POPF, any complication, and serious complication. Outcomes were compared between MELD score strata (< 11 vs. ≥ 11) as established by the United Network for Organ Sharing (UNOS). Multivariable logistic regression models were constructed to examine the risk-adjusted impact of MELD score on outcomes. RESULTS: A total of 7580 PDs and 3295 DPs had evaluable MELD scores. Of these, 1701 PDs and 223 DPs had a MELD score ≥ 11. PDs with MELD ≥ 11 exhibited higher risk for mortality (OR = 2.07, p < 0.001), discharge not-to-home (OR = 1.26, p = 0.005), and transfusion (OR = 1.7, p < 0.001). DP patients with MELD ≥ 11 demonstrated prolonged LOS (OR = 1.75, p < 0.001), discharge not-to-home (OR = 1.83, p = 0.01), and transfusion (OR = 2.78, p < 0.001). In PD, MELD ≥ 11 was independently predictive of 30-day mortality (OR = 1.69, p = 0.007) and transfusion (OR = 1.55, p < 0.001). In DP, MELD ≥ 11 was independently predictive of prolonged LOS (OR = 1.42, p = 0.026) and transfusion (OR = 2.3, p < 0.001). CONCLUSION: A MELD score ≥ 11 is associated with a near twofold increase in the odds of mortality following pancreatoduodenectomy. The MELD score is an objective assessment that aids in risk-stratifying patients undergoing pancreatectomy.

A Multisite Case Study of Caregiver Advise, Record, Enable Act Implementation.

BACKGROUND AND OBJECTIVES: The Commonwealth of Pennsylvania passed the Caregiver Advise, Record, Enable (CARE) Act on April 20, 2016. We designed a study to explore early implementation at a large, integrated delivery financing system. Our goal was to assess the effects of system-level decisions on unit implementation and the incorporation of the CARE Act's three components into routine care delivery. RESEARCH DESIGN AND METHODS: We conducted a multisite, ethnographic case study at three different hospitals' medical-surgical units. We conducted observations and semi-structured interview to understand the implementation process and the approach to caregiver identification, notification, and education. We used thematic analysis to code interviews and observations and linked findings to the Promoting Action on Research Implementation in Health Services framework. RESULTS: Organizational context and electronic health record capability were instrumental to the CARE Act implementation and integration into workflow. The implementation team used a decentralized strategy and a variety of communication modes, relying on local hospital units to train staff and make the changes. We found that the system facilitated the CARE Act implementation by placing emphasis on the documentation and charting to demonstrate compliance with the legal requirements. DISCUSSION AND IMPLICATIONS: General acute hospitals will be making or have made similar decisions on how to operationalize the regulatory components and demonstrate compliance with the CARE Act. This study can help to inform others as they design and improve their compliance and implementation strategies.

Association of Mentorship and a Formal Robotic Proficiency Skills Curriculum With Subsequent Generations' Learning Curve and Safety for Robotic Pancreaticoduodenectomy.

Importance: Learning curves are unavoidable for practicing surgeons when adopting new technologies. However, patient outcomes are worse in the early stages of a learning curve vs after mastery. Therefore, it is critical to find a way to decrease these learning curves without compromising patient safety. Objective: To evaluate the association of mentorship and a formal proficiency-based skills curriculum with the learning curves of 3 generations of surgeons and to determine the association with increased patient safety. Design, Setting, and Participants: All consecutive robotic pancreaticoduodenectomies (RPDs) performed at the University of Pittsburgh Medical Center between 2008 and 2017 were included in this study. Surgeons were split into generations based on their access to mentorship and a proficiency-based skills curriculum. The generations are (1) no mentorship or curriculum, (2) mentorship but no curriculum, and (3) mentorship and curriculum. Univariable and multivariable analyses were used to create risk-adjusted learning curves by surgical generation and to analyze factors associated with operating room time, complications, and fellows completing the full resection. The participants include surgical oncology attending surgeons and fellows who participated in an RPD at University of Pittsburgh Medical Center between 2008 and 2017. Main Outcomes and Measures: The primary outcome was operating room time (ORT). Secondary outcomes were postoperative pancreatic fistula and Clavien-Dindo classification higher than grade 2. Results: We identified 514 RPDs completed between 2008 and 2017, of which 258 (50.2%) were completed by first-generation surgeons, 151 (29.3%) were completed by the second generation, and 82 (15.9%) were completed by the third generation. There was no statistically significant difference between groups with respect to age (66.3-67.3 years; P = .52) or female sex (n = 34 [41.5%] vs n = 121 [46.9%]; P = .60). There was a significant decrease in ORT (P < .001), from 450.8 minutes for the first-generation surgeons to 348.6 minutes for the third generation. Additionally, across generations, Clavien-Dindo classification higher than grade 2 (n = 74 [28.7%] vs n = 30 [9.9%] vs n = 12 [14.6%]; P = .01), conversion rates (n = 18 [7.0%] vs n = 7 [4.6%] vs n = 0; P = .006), and estimated blood loss (426 mL vs 288.6 mL vs 254.7 mL; P < .001) decreased significantly with subsequent generations. There were no significant differences in postoperative pancreatic fistula. Conclusions and Relevance: In this study, ORT, conversion rates, and estimated blood loss decreased across generations without a concomitant rise in adverse patient outcomes. These findings suggest that a proficiency-based curriculum coupled with mentorship allows for the safe introduction of less experienced surgeons to RPD without compromising patient safety.

Proficiency-based training and credentialing can improve patient outcomes and decrease cost to a hospital system.

BACKGROUND: While proficiency-based robotic training has been shown to enhance skill acquisition, no studies have shown that training leads to improved outcomes or quality measures. METHODS: Board-certified general surgeons participated in an optional proficiency-based robotic training curriculum and outcomes from robotic hernia cases were analyzed. Multivariable analysis was performed for operative times to adjust for patient and surgical variables. RESULTS: Six out of 16 (38%) surgeons completed training and 210 robotic hernia cases were analyzed. Longer operative times were associated with bilateral repairs (observed-to-expected operative time ratio [OTR] = 1.41, p < 0.001) and incarceration (OTR = 1.24, p = 0.006), while female patients (OTR = 0.87, p = 0.001) and increasing chronologic case order (OTR = 0.94, p < 0.001) were associated with shorter operative times. Surgeons who completed robotic training achieved shorter OTRs than those who did not (p = 0.03). Comparing non-risk adjusted hospital costs, trainees had an average of $1207 in savings (20% reduction) per robotic hernia case. CONCLUSIONS: A structured proficiency-based robotics training curriculum is an effective way to reduce operative times and costs.

University of Pittsburgh Medical Center Home Transitions Multidisciplinary Care Coordination Reduces Readmissions for Older Adults.

OBJECTIVES: To compare rates of 30- and 90-day hospital readmissions and observation or emergency department (ED) returns of older adults using the University of Pittsburgh Medical Center (UPMC) Health Plan Home Transitions (HT) with those of Medicare fee-for-service (FFS) controls without HT. DESIGN: Retrospective cohort study. SETTING: Analysis of home health and hospital records from 8 UPMC hospitals in Allegheny County, Pennsylvania, from July 1, 2015, to April 30, 2017. PARTICIPANTS: HT program participants (n=1,900) and controls (n=1,300). INTERVENTION: HT is a care transitions program aimed at preventing readmission that identifies older adults at risk of readmission using a robust inclusion algorithm; deploys a multidisciplinary care team, including a nurse practitioner (NP), a social worker (SW), or both; and provides a multimodal service including personalized care planning, education, treatment, monitoring, and communication facilitation. MEASUREMENT: We used multivariable logistic regression to determine the effects of HT on the odds of hospital readmission and observation or ED return, controlling for index admission participant characteristics and home health process measures. RESULTS: The adjusted odds of 30-day readmission was 0.31 (95% confidence interval (CI) = 0.11-0.87, P = .03) and of 90-day readmission was 0.47 (95% CI=CI = 0.26-0.85, P = .01), for participants at medium risk of readmission in HT who received a team visit. The adjusted odds of 30-day readmission was 0.29 (95% CI = 0.10-0.83, P = .02) for participants at high risk of readmission in HT who received a team visit. The adjusted odds of 30-day observation or ED return was 1.90 (95% CI = 1.28-2.82, P = .001) for participants at medium risk of readmission in HT who received a team visit. CONCLUSION: The HT program may be associated with lower odds of 30- and 90-day hospital readmission and counterbalancing higher odds of observation or ED return. J Am Geriatr Soc 67:156-163, 2019.

Limitations of patient experience reports to evaluate physician quality in spine surgery: analysis of 7485 surveys.

OBJECTIVEThe Clinician and Group Consumer Assessment of Healthcare Providers and Systems (CG-CAHPS) is a standardized patient experience survey that is used to evaluate the quality of care delivered by physicians. The authors sought to determine which factors influenced CG-CAHPS scores for spine surgery, and compare them to their cranial-focused cohorts.METHODSA retrospective study of prospectively obtained data was performed to evaluate CG-CAHPS scores. Between May 2013 and May 2017, all patients 18 years of age or older with an outpatient encounter with a neurosurgeon (5 spine-focused neurosurgeons and 20 cranial-focused neurosurgeons) received a CG-CAHPS survey. Three domains were assessed: overall physician rating, likelihood to recommend, and physician communication. Statistical analyses were performed using chi-square tests.RESULTSSeven thousand four hundred eighty-five patient surveys (2319 spine and 5166 cranial) were collected from patients presenting to the outpatient offices of an attending neurosurgeon. Analysis of the overall physician rating showed that 81.1% of spine neurosurgeons received a "top-box" score (answers of "yes, definitely"), whereas 86.2% of cranial neurosurgeons received a top-box response (p < 0.001). A similar difference was observed with the domains of "likelihood to recommend" and "physician communication." Overall physician rating was also significantly influenced by the general and mental health of the patients surveyed (p < 0.001). For spine surgeons seeing patients at more than one facility, the scores with respect to location were also significantly different in all domains for each individual provider (p < 0.001).CONCLUSIONSOverall, spine-focused neurosurgeon ratings differed significantly from those of cranial-focused neurosurgical subspecialty providers. Office location also affected provider ratings for spine neurosurgeons. These results suggest that physician ratings obtained via patient experience surveys may be representative of factors aside from just the quality of physician care provided. This information should be considered as payers, government, and health systems design performance programs based on patient experience scores.

Effect of the Hospital Elder Life Program on Risk of 30-Day Readmission.

OBJECTIVES: To compare rates of 30-day readmission between hospital units with a Hospital Elder Life Program (HELP) and control units without HELP. DESIGN: Retrospective cohort study. SETTING: The study took place from July 1, 2013, to June 30, 2014, at the University of Pittsburgh Medical Center Shadyside, a 520-bed community teaching hospital that has used HELP since 2002. Eight medical and surgical units with HELP were compared with 10 medical and surgical units without HELP. PARTICIPANTS: During the study period, HELP units, had 4,794 patients aged 70 and older, and usual care units had 2,834. INTERVENTION: HELP is a multifactorial, multidisciplinary program that provides targeted interventions for delirium risk factors in at-risk individuals in collaboration with bedside staff. MEASUREMENTS: Mixed-effects Poisson regression models were used to estimate the adjusted incident risk ratio for 30-day readmission between HELP and usual care units for the overall cohort and for the subgroup of individuals discharged home, with or without services. RESULTS: Patients on HELP units were more likely than those in usual care units to be older, female, and black and had an unadjusted readmission rate of 16.9%, versus 18.9% for patients on control units. The adjusted risk of readmission was 0.83 (95% confidence interval (CI) = 0.73-0.94, P = .003) for HELP unit patients overall and 0.74 (95% CI = 0.63-0.87, P < .001) for HELP unit patients discharged to home with or without services. CONCLUSION: The HELP program is associated with lower risk of 30-day hospital readmission overall and for the subgroup of individuals discharged to home. Prospective studies are needed to confirm these observations.