Case Mix Complexity Research Articles

Learning Curve for Robotic Colorectal Surgery.

With the increasing adoption of robotic surgery in clinical practice, institutions intending to adopt this technology should understand the learning curve in order to develop strategies to help its surgeons and operating theater teams overcome it in a safe manner without compromising on patient care. Various statistical methods exist for the analysis of learning curves, of which a cumulative sum (CUSUM) analysis is more commonly described in the literature. Variables used for analysis can be classified into measures of the surgical process (e.g., operative time and pathological quality) and measures of patient outcome (e.g., postoperative complications). Heterogeneity exists in how performance thresholds are defined during the interpretation of learning curves. Factors that influence the learning curve include prior surgical experience in colorectal surgery, being in a mature robotic surgical unit, case mix and case complexity, robotic surgical simulation, spending time as a bedside first assistant, and being in a structured training program with proctorship.

An Analysis of the Standardized Infection Ratio in California from 2015 to 2019: A Publicly Reported, Validated Measure of Hospital Case-mix Complexity and Quality for Surgical Site Infections in Hip Arthroplasty

The Standardized Infection Ratio (SIR), developed by the National Healthcare Safety Network (NHSN), is a validated healthcare quality outcome measure utilized by the California Department of Public Health (CDPH). Our primary goal was to use information from the SIR as measures of risk-adjusted surgical case-mix complexity and Healthcare Associated Infection (HAI) quality for surgical site infections (SSIs) in hip prosthesis (HPRO) surgery. We acquired NHSN SSI data files for HPRO surgery from 330 acute care hospitals. We categorized hospitals into 5 types (teaching, rural, community low volume, community medium volume, and community high volume) and sorted hospitals by procedure count, generating volume terciles. We multiplied each SIR and 95% confidence limits by a scale factor to allow for a comparison to the average SIR in California for the study period. The highest and lowest expected infection rates (case-mix complexity) were found in teaching hospital (0.86%) and community, high- volume hospitals (0.56%). When all non-teaching hospitals were combined, teaching hospitals treated a higher case complexity (95% Confidence Limit (CL): 0.7713 to 0.9727) than non-teaching hospitals (95% CL 0.5774, 0.6518). The lowest and highest SIR values were seen in community high volume (0.78) and rural hospitals, (1.38). The lowest- volume hospitals performed significantly worse (SIR 1.15: 95%CL 1.058-1.256) than the highest- volume hospitals (SIR 0.83: 95% CL 0.747-0.920). The SIR model developed by NHSN provides important public information about risk-adjusted surgical case-mix complexity and hospital quality for SSIs that incorporates parameters that may more accurately account for technical challenges in HPRO surgery.

Factors driving differences in the adoption of quality management practices among hospitals: A two-phase, sequential mixed-methods analysis.

Although all hospitals aim to deliver high-quality care, there is considerable variation in their adoption of quality management (QM) practices. Organizational and environmental factors are known to drive strategic decision-making in hospitals, but their impact on the adoption of QM practices remains unclear. Our study aims to identify multiple organizational and environmental factors that explain variation in the adoption of QM practices among hospitals and to explore mechanisms underlying these relationships. We conducted a two-phase, sequential mixed-methods study of German acute care hospitals. The quantitative phase used between-effects regressions to identify factors explaining variation in the number of QM practices adopted by hospitals from 2015 to 2019. The qualitative phase used semistructured interviews with quality managers to gain in-depth insights. The number of QM practices adopted by a hospital was significantly associated with factors like hospital size and the presence of an emergency department or QM steering committee. Our qualitative findings highlighted potential mechanisms such as the presence of an emergency department serving as a proxy for organizational complexity or urgency of case-mix. We provide an overview of factors driving QM adoption in hospitals, extending beyond the focus on single factors in previous research. Future studies could explore additional factors highlighted by our interviewees. Our results can inform interventions to strengthen QM in hospitals and guide future research on this topic.

Catheterization for Congenital Heart Disease Adjustment for Risk Method II.

Current metrics used to adjust for case mix complexity in congenital cardiac catheterization are becoming outdated due to the introduction of novel procedures, innovative technologies, and expanding patient subgroups. This study aims to develop a risk adjustment methodology introducing a novel, clinically meaningful adverse event outcome and incorporating a modern understanding of risk. Data from diagnostic only and interventional cases with defined case types were collected for patients ≤18 years of age and ≥2.5 kg at all Congenital Cardiac Catheterization Project on Outcomes participating centers. The derivation data set consisted of cases performed from 2014 to 2017, and the validation data set consisted of cases performed from 2019 to 2020. Severity level 3 adverse events were stratified into 3 tiers by clinical impact (3a/b/c); the study outcome was clinically meaningful adverse events, severity level ≥3b (3bc/4/5). The derivation data set contained 15 224 cases, and the validation data set included 9462 cases. Clinically meaningful adverse event rates were 4.5% and 4.2% in the derivation and validation cohorts, respectively. The final risk adjustment model included age <30 days, Procedural Risk in Congenital Cardiac Catheterization risk category, and hemodynamic vulnerability score (C statistic, 0.70; Hosmer-Lemeshow P value, 0.83; Brier score, 0.042). CHARM II (Congenital Heart Disease Adjustment for Risk Method II) risk adjustment methodology allows for equitable comparison of clinically meaningful adverse events among institutions and operators with varying patient populations and case mix complexity performing pediatric cardiac catheterization.

The socioeconomic distribution of life expectancy and healthy life expectancy in Chile

BackgroundLife expectancy (LE) has usually been used as a metric to monitor population health. In the last few years, metrics such as Quality-Adjusted-Life-Expectancy (QALE) and Health-Adjusted-Life- Expectancy (HALE) have gained popularity in health research, given their capacity to capture health related quality of life, providing a more comprehensive approach to the health concept. We aimed to estimate the distribution of the LE, QALEs and HALEs across Socioeconomic Status in the Chilean population.MethodsBased on life tables constructed using Chiang II´s method, we estimated the LE of the population in Chile by age strata. Probabilities of dying were estimated from mortality data obtained from national registries. Then, life tables were stratified into five socioeconomic quintiles, based on age-adjusted years of education (pre-school, early years to year 1, primary level, secondary level, technical or university). Quality weights (utilities) were estimated for age strata and SES, using the National Health Survey (ENS 2017). Utilities were calculated using the EQ-5D data of the ENS 2017 and the validated value set for Chile. We applied Sullivan´s method to adjust years lived and convert them into QALEs and HALEs.ResultsLE at birth for Chile was estimated in 80.4 years, which is consistent with demographic national data. QALE and HALE at birth were 69.8 and 62.4 respectively. Men are expected to live 6.1% less than women. However, this trend is reversed when looking at QALEs and HALEs, indicating the concentration of higher morbidity in women compared to men. The distribution of all these metrics across SES showed a clear gradient in favour of a better-off population-based on education quintiles. The absolute and relative gaps between the lowest and highest quintile were 15.24 years and 1.21 for LE; 18.57 HALYs and 1.38 for HALEs; and 21.92 QALYs and 1.41 for QALEs. More pronounced gradients and higher gaps were observed at younger age intervals.ConclusionThe distribution of LE, QALE and HALEs in Chile shows a clear gradient favouring better-off populations that decreases over people´s lives. Differences in LE favouring women contrast with differences in HALEs and QALEs which favour men, suggesting the need of implementing gender-focused policies to address the case-mix complexity. The magnitude of inequalities is greater than in other high-income countries and can be explained by structural social inequalities and inequalities in access to healthcare.

Alignment of RVU Targets With Operating Room Block Time.

Surgeon productivity is measured in relative value units (RVUs). The feasibility of attaining RVU productivity targets requires surgeons to have enough allocated block time to generate RVUs. However, it is unknown how much block time is required for surgeons to attain specific RVU targets. We aimed to estimate the effect of surgeon and practice environment characteristics (SPECs) on block time needed to attain fixed RVU targets. We computationally simulated individual surgeons' annual caseloads under a variety of SPECs in the following way. First, empirical case data were sampled from ACS NSQIP in accordance with surgeon specialty, case-mix complexity, and RVU target. Surgeons' operating schedules were then constructed according to the block length, turnover time, and scheduling flexibility of the practice environment. These 6 SPECs were concurrently varied over their ranges for a 6-way sensitivity analysis. Annual operating schedules for 60,000,000 surgeons were simulated. The number of blocks required to attain RVU targets varied significantly with surgeon specialty and increased with increased case-mix complexity, increased turnover time, and decreased scheduling flexibility. Intraspecialty variation in block requirement with variation in environmental characteristics exceeded interspecialty variation with fixed environmental characteristics. Multivariate linear models predicted block utilization across surgical specialties with consideration for the stated factors. An online tool is shared with which to apply these results to one's particular practice. Block time required to attain RVU targets varies widely with SPECs; intraspecialty variation exceeds interspecialty variation. The feasibility of attaining RVU targets requires alignment between targets and allocated operating time with consideration for surgical specialty and other practice conditions.

The Relationship Between Postoperative Complications and Children's Quality of Life: A Mediation Analysis to Explore the Role of Family Factors.

To explore whether postoperative morbidities after pediatric cardiac surgery affected children's health-related quality of life (HRQOL) at 6 months, through potentially modifiable parental psychological factors. We undertook a mediation analysis, to explore the causal pathway, based on data from a prospective, case-matched cohort study. Six hundred sixty-six children undergoing cardiac surgery. Five centers in the United Kingdom. No intervention. Cases of morbidity were identified early after pediatric cardiac surgery, and matched controls with no morbidities were identified at discharge. Four mediators were assessed at 6 weeks after surgery, using the PedsQL Family Impact Module (Parent HRQOL and Family Function) and the PHQ-4 (Anxiety and Depression). The study outcome of child HRQOL was assessed at 6 months with the PedsQL. Of 666 children, 408 (65% of those surviving) contributed to the primary outcome. Children who had extracorporeal life support (ECLS) ( n = 11) ( p < 0.05) and multiple morbidities ( n = 62) ( p < 0.01) had worse 6-month HRQOL than those with a single morbidity ( n = 125) or no morbidity ( n = 209). After adjustment for case mix complexity and sociodemographic variables, there were significant indirect effects of parent HRQOL at 6 weeks, on the PedsQL Total Score (ECLS, -5.1 [-8.4 to -1.8]; p = 0.003; multiple morbidities, -2.1 [-3.7 to -0.5]; p = 0.01), PedsQL Physical Score (ECLS, -5.1 [-8.7 to -1.4]; p = 0.007; multiple morbidities, -2.1 [-3.8 to -0.4]; p = 0.016), and PedsQL Psychosocial Score (ECLS: -5.3 [-8.7 to -1.8); p = 0.003; multiple morbidities, -2.2 [-3.9 to -0.5]; p = 0.01). The proportion of the total effect of ECLS and multiple morbidity on the study outcomes mediated through parent HRQOL ranges between 18% and 61%. There was no evidence that the other three mediators had indirect effects on the study outcome. Parental HRQOL at 6 weeks after surgery contributes to child HRQOL at 6 months, among those with the severest types of morbidity, and as such should be a target for future interventions.

34. Machine learning methods applied to audit of surgical margins after curative surgery for facial (non-melanoma) skin cancer

Most surgical specialities have attempted to address concerns about unfair comparison of outcomes by 'risk-adjusting' data when reporting speciality-specific outcomes that are indicative of quality of care. We explore predicting positive margin status, following excision of facial non-melanoma skin cancer, so that outcome audit that will account for complexity of case-mix, is possible.

Changes in Practice/Outcomes of Pediatric/Congenital Catheterization in Response to the First Wave of COVID

BackgroundThe COVID-19 pandemic has posed tremendous stress on the health care system. Its effects on pediatric/congenital catheterization program practice and performance have not been described. ObjectivesThe purpose of this study was to evaluate how case volumes, risk-profile, and outcomes of pediatric/congenital catheterization procedures changed in response to the first wave of COVID-19 and after that wave. MethodsA multicenter retrospective observational study was performed using Congenital Cardiac Catheterization Project on Outcomes Registry (C3PO) data to study changes in volume, case mix, and outcomes (high-severity adverse events [HSAEs]) during the first wave of COVID (March 1, 2020, to May 31, 2020) in comparison to the period prior to (January 1, 2019, to February 28, 2020) and after (June 1, 2020, to December 31, 2020) the first wave. Multivariable analyses adjusting for case type, hemodynamic vulnerability, and age group were performed. Hospital responses to the first wave were captured with an electronic study instrument. ResultsDuring the study period, 12,557 cases were performed at 14 C3PO hospitals (with 8% performed during the first wave of COVID and 32% in the postperiod). Center case volumes decreased from a median 32.1 cases/month (IQR: 20.7-49.0 cases/month) before COVID to 22 cases/month (IQR: 13-31 cases/month) during the first wave (P = 0.001). The proportion of cases with risk factors for HSAE increased during the first wave, specifically proportions of infants and neonates (P < 0.001) and subjects with renal insufficiency (P = 0.02), recent cardiac surgery (P < 0.001), and a higher hemodynamic vulnerability score (P = 0.02). The observed HSAE risk did not change significantly (P = 0.13). In multivariable analyses, odds of HSAE during the first wave of COVID (odds ratio: 0.75) appeared to be lower than that before COVID, but the difference was not significant (P = 0.09). ConclusionsDespite increased case-mix complexity, C3PO programs maintained, if not improved, their performance in terms of HSAE. Exploratory analyses of practice changes may inform future harm-reduction efforts.

Prediction Algorithms: Is Peer Review Enough?

Prediction Algorithms: Is Peer Review Enough?

Intermediate care units in progressive patient care model: a systematic literature review

&#x0D; Background: Progressive patient care (PPC) has been defined as a systematic classification and segregation of patients based on their medical and nursing needs. Aim of the present research was to perform a systematic literature review about existing medical intermediate care unit organizational models and their performance strengths and weaknesses with a specific focus on Italian implementation, respect to US model.&#x0D; Methods: Databases PubMed, Cinahl, Google and Google Scholar were searched until September 2017. The search was limited to Italian and English studies. All study design are included in the review.&#x0D; Results: Ten studies were included in the review. The American studies showed, after the PPC reorganization, an increase in level of satisfaction and nursing care, a reduction in average length of stay, costs and tensions between nurses and an improvement in nurse-physician communication. An Italian study reported the results of a project carried out in three case studies (Forlì, Foligno and Pontedera hospital), redesigning hospital patient flow logistics around the concept of intensity of care: in all three cases, after the reorganization, an increase in bed occupancy rate (before: 71%,81%,65%; after: 78%,84%,82%, respectively) and in hospital case-mix complexity (average DRG weight - before: 0.99,1.07,1.12; after: 1.19,1.09,1.61, respectively) and a reduction in turn-over ratio (before: 2.5,1.4,2.8; after: 1.5,1.2,1.7, respectively) was recorded. Considering Italian healthcare professionals’ point of view, majority of internists supported a hospital remodeling according to PPC model.&#x0D; Conclusions: The PPC model, theorized in US, has found several applications in Italian regional realities. Improvements in quality of care, appropriateness and productivity in healthcare facilities, that adopted the PPC program, were observed.&#x0D;

Machine learning methods applied to audit of surgical margins after curative surgery for head and neck cancer

Most surgical specialties have attempted to address concerns about the unfair comparison of outcomes by ‘risk-adjusting’ data to benchmark specialty-specific outcomes that are indicative of quality of care. We explore the ability to predict for positive margin status so that effective benchmarking that will account for complexity of case mix is possible. A dataset of care episodes recorded as a clinical audit of margin status after surgery for head and neck squamous cell carcinoma (n=1316) was analysed within the Waikato Environment for Knowledge Analyisis (WEKA) machine learning programme. The outcome was a classification model that can predict for positivity of tumour margins (defined as less than 1mm) using data on preoperative demographics, operations, functional status, and tumour stage. Positive resection margins of less than 1mm were common, and varied considerably between treatment units (19%-29%). Four algorithms were compared to attempt to risk-adjust for case complexity. The 'champion' model was a Naïve Bayes classifier (AUROC 0.72) that suggested acceptable discrimination. Calibration was good (Hosmer-Lemershow goodness-of-fit test p=0.9). Adjusted positive margin rates are presented on a funnel plot. Subspecialty groups within oral and maxillofacial surgery are seeking metrics that will allow for meaningful comparison of the quality of care delivered by surgical units in the UK. To enable metrics to be effective, we argue that they can be modelled so that meaningful benchmarking, which takes account of variation in complexity of patient need or care, is possible.

Out-of-hours calls in clinical microbiology: the when, the why and from whom.

Microbiology services provided to hospitals must be delivered 24 h a day. In addition to during routine so-called 'office hours', clinical microbiologists have to provide an on-call service 7 days a week. However, there are few data on what that involves and how the service is delivered. I reviewed the source, reason for, grade of staff from whom the call came and the need for any follow-up, over an 11-year period using a pro-forma, that had been used to review data before this time period. Details were available for 90% of calls received, and data from 809 calls were analysed. The sources of calls were most commonly from medicine specialties [163/809 (20.1%)], neurosurgery (which is a national referral centre) [148/809 (18.3%)] and the intensive care unit [143/809 (17.7%)]. The number of calls received between 23.00 hours and 07.00 hours was 107 (13.2%). Just over half of calls, i.e. 440/809 (54.6%), were related to treatment; 247/809 (30.5%) were for advice on diagnosis; and 79/809 (9.8%) were related to infection prevention and control (IPC) issues. Registrars (a senior training grade) accounted for 492/809 (60.8%) of calls, and 64/809 (7.9%) came from nurses mainly related to IPC matters. Overall, 25.4% (206/809) of calls required follow-up the next day but this increased from 4.5% in 2013 to 67.6% in 2018. The nature of calls received by a clinical microbiologist out-of-hours is varied and may be increasing due to the complexity of case mix and changes in medical staffing. Professional and other organisations would do well to review such workload when deciding on staffing levels and service planning, given increasing public and patient expectations, and the trend towards the centralisation/consolidation of laboratory diagnostic services.

In-House Cardiology Consultation Reduces Readmission Rates and Costs for Patients in Skilled Nursing Facilities: Lessons Learned upon Completion of 3 Years in the Heart Failure Bundle Payment Care Improvement Initiative

Background Heart failure (HF) patients admitted to skilled nursing facilities (SNFs) have poor clinical outcomes despite immense resource utilization. CMS developed the Bundled Payments for Care Improvement (BPCI) program, providing shared savings to participating providers for 90-day episodes of care with the purpose of improving quality and lowering costs. SNF-based cardiology consultation for HF patients was shown in a pilot study to reduce costs and 90-day readmission rates over an initial 2-year enrollment period. This study evaluates the comparative impact of that SNF-based cardiologist-led HF program on readmission rates and costs after completion of 3 years in the BPCI Model 3 program. Methods We performed a retrospective analysis using Medicare claims data of BPCI-enrolled HF patients admitted to St. Joseph's Center (SJC), a Genesis Healthcare SNF with a cardiologist-led HF program (HFP). Data were collected from October 2015 to September 2018. Readmission rates and cost savings vs CMS-determined cost targets were compared between SJC and 31 other enrolled SNFs: 24 of which had no HFP; 7 of which had a HFP employing dietary, rehabilitation, social work and medical staff, with limited to no direct cardiology consultation. Cardiology consultation was requested for HF patients at SJC with unstable vital signs, refractory volume overload or symptoms, or cardiac limitations to rehabilitation. Weekly cardiology rounds provided HF management within the context of achieving clinical stability, rehabilitation goals and preparing for community discharge. The cardiologist identified patients at high risk for readmission, and multidisciplinary monitoring and management for those patients was intensified. Results There were 835 total HF episodes in the 3-year evaluation period: 22 were admitted to SJC; 291 were admitted to facilities with a HFP; and 522 to facilities without a HFP. The case mix at SJC included more patients with major complications and co-morbid conditions (77% vs 65% for all other SNFs, and 60% for SNFs with a HFP). Compared to other facilities, hospital readmission from SJC was significantly lower in the first 30 days after HF hospitalization (4.5% vs 23.6% (p = .018) for all other SNFs; and 23.7% (p = .019) for SNFs with a HFP), and remained lower for the 90-day episode duration (27.3% vs 44.8% (p = .052) for all other SNFs; and 48.8% (p = .026) for SNFs with a HFP). SJC achieved a higher margin of cost savings compared to facilities without a consulting cardiologist (28% vs 11%). Conclusions Incorporating a cardiologist into SNF HF teams consistently reduced re-hospitalizations and costs for HF episodes over a 3-year period. Further evaluation is needed to understand why outcomes among SNFs with standard HF programs were worse despite a lower case mix complexity. Weekly assessments and clinical management incorporating patient-centered rehabilitation goals may improve outcomes for this vulnerable HF population.

Developing the competency of ‘collaborative clinical practice’

This article was migrated. The article was not marked as recommended. With the increasing complexity of healthcare delivery and patient case mix, and the aging population, health professionals are expected to function more often and more effectively as members of multidisciplinary teams. Competency based medical education (CBME) advocates that the professional development of doctors should be fostered from the start of medical school through to medical practice and with continuing professional development. Strategies for developing teamwork among health professionals and students range from minimal, implicit to explicit (Earnest et al., 2017). Considering this continuum of medical education and the spectrum of educational strategies, we propose a framework for the programmatic approach which can be used in developing competence in 'collaborative clinical practice'.

Access to Interventional Radiology Services in Small Hospitals and Rural Communities: An ACR Membership Intercommission Survey

PurposeTo evaluate the status of interventional radiology (IR) staffing, recruitment, and retention in the United States, specifically as they apply to small hospitals and rural communities. Materials and MethodsA 22-question survey was created by an ACR intercommission workgroup and circulated via e-mail to ACR members who self-identified as a “group practice leader,” “general radiologist,” “interventional radiologist,” or “abdominal radiologist.” Contingency tables were constructed, and bivariate analyses were performed to assess overall responses and the distribution of responses among specific groups of respondents. ResultsA total of 1,005 e-mail recipients completed the survey. A statistically significant greater proportion of responders from rural hospitals (versus nonrural hospitals) answered that (1) their group falls short or far short of meeting demand for IR services (29.1% versus 14.3%), (2) they had difficulty recruiting IR physicians to their practice (67% versus 40.6%), and (3) they had difficulty retaining IR physicians (40% versus 29%). The most frequently reported reasons for difficulty recruiting were that IR-trained physicians “do not want to do diagnostic work” (56.2%) and “do not want to practice in a small or rural setting” (48.8%). A greater proportion of respondents from rural hospitals perceived that they had difficulty retaining IR physicians because of perceived inadequate “complexity of case mix” (67.5%) or “number of cases” (66.1%). ConclusionSmall hospitals and rural communities experience greater difficulty recruiting and retaining IR physicians and meeting IR service demands compared with their nonrural counterparts.

Measurement of health organisation performance across multiple sector services: a population health analytic perspective

Introduction: In measuring the activity and indeed the performance of health organisations it is important to consider not only the case-mix of the organisation and technical efficiency, but also what inter-dependencies may exist between organisations, or whether they are covering different services and extent of services. This study seeks to measure and provide a population health analytic approach to recognising the effects of substitution and overlap of activities of primary and secondary care. Challenges to measure true performance of organisations exist where sectors of care exist across different organisations, and where health care is divided across silos and are reviewed without consideration of interrelationships. In addition, with the increased policies worldwide to introduce integrated health services e.g. accountable care organisations, local health community and population health programs, assessing cost and health quality improvements will need an adequate a framework to understand where improvements are attributed across multiple contributing organisations. Methods: The data sources include multiple studies from different countries. Primary Care and secondary care data were combined to create population databases, and casemix measurement was made using the Johns Hopkins ACG System. The distribution of the populations were analysed observing the share of activity and cost between primary, outpatient and inpatient services. The triple aim reporting framework suggested by Seow 2014 will be adapted to look at both temporal changes in cost distribution by health sector, and looking to identify and classify different organisation models. The Johns Hopkins ACG Adjusted Clinical Groups system was used to control for casemix complexity and multimorbidity. Results: Analysis of total costs across all sectors inpatient, outpatient, emergency care and primary care showed the increased costs associated with higher complexity and multimorbid patients. The distribution of utilisation and cost were different according to the complexity of patients but also by organisation. For example, the proportion of spend on primary care services was generally higher for lower complexity patients, with the proportion reducing with increased complexity, and in association, the increased spend on hospital services could be seen as complexity increased. But regional analyses also highlighted that these proportions of spend were different even when casemix complexity was held constant. The population level analyses showed different results with respect to cost efficiency than those shown in individual sectors. Discussion: In measuring organisational performance it is important to consider the extent of vertical integration in health services in fully understanding the cost effectiveness and efficiency of health systems. Isolating individual sectors of health care for measurement may lead to incorrect interpretation of results where interdependencies between services across different sectors exist. Policy makers need to be aware of the effect of activity shifting between health sectors, which can lead to increased complexity in all sectors, increases in average costs per sector, whilst the potential lower costs and convenience to patients are unmeasured Technical v Allocative efficiency. Casemix adjustment is an important consideration in measuring health care organisations, but to reduce confounding the inter and intra organisational dynamics and dependencies need to be considered.

In-House Cardiology Consultation Reduces Readmission Rates and Costs for Patients in Skilled Nursing Facilities: 2 Years’ Experience in the Heart Failure Bundle Payment Care Improvement Initiative

Background Heart failure (HF) patients admitted to skilled nursing facilities (SNFs) are vulnerable to poor outcomes. CMS developed the Bundled Payments for Care Improvement Initiative (BPCI) which provides participating providers shared savings based on costs for 90-day episodes of care with the purpose of improving quality and cost-effectiveness. Greater availability of clinical staff has shown promise in improving outcomes for SNF patients. The effect of cardiology consultation for SNF patients with HF has not been evaluated. This study evaluates the impact of a SNF-based cardiologist-led HF program on 90-day readmission rate and resource utilization. Methods We performed a retrospective analysis using Medicare claims data of BPCI-enrolled HF patients admitted to St. Joseph's Center (SJC), a Genesis Healthcare SNF with a cardiologist-led HF program. Data were collected from October 2015 to September 2017. Readmission rates and cost savings versus CMS-determined cost targets were compared between SJC and 31 other enrolled SNFs, 24 of which had no HF program, 7 of which had standard programs composed of a multidisciplinary team of dietary, rehabilitation, social work and clinical staff. The SJC program additionally instructed staff to request cardiac consultation for patients with unstable vital signs, refractory volume overload or symptoms, or cardiac limitations to rehabilitative therapy. Cardiology rounds were conducted weekly and management was provided in the context of achieving subacute rehabilitation goals, clinical stability, and preparing for community discharge. The cardiologist identified and alerted staff to patients deemed high risk for readmission, and multidisciplinary monitoring and management for those patients was intensified. Results There were 602 total HF episodes in the 24-month evaluation period. Seventeen patients were admitted to SJC; 218 patients to a facility with a HF program; and 367 patients to a facility without a HF program. The case mix complexity at SJC included a higher percentage of patients with major complications and comorbid conditions (71% vs 60% for all other SNFs and 64% for SNFs with HF programs). More than 50% of patients at SJC prompted specialty consultation. Compared to other facilities, the percentage of SJC patients readmitted in the 90-day post HF hospitalization period was significantly lower (23.5% vs 43.4% (p = .052) for all other SNFs; and 48.2% (p = .025) for SNFs with a non-cardiologist based HF program). SJC achieved a higher margin of cost savings compared to facilities that did not have a consulting cardiologist (39% vs 15%). Conclusion Patient-centered cardiology consultation for high risk HF patients may effectively reduce re-hospitalizations and resource utilization within SNFs. These results identify a potential gap in care for this vulnerable cohort of HF patients and suggest that incorporating a cardiologist into the management team may impact outcomes.

Antecedents of Information Systems Sourcing Strategies in U.S. Hospitals: A Longitudinal Study

The popular press has long used the terms single-sourcing and multisourcing (also known as best of breed) to describe organizations' sourcing strategies. Whereas there is an implicit understanding of these terms, no research has quantified what distinguishes one sourcing configuration from another or what institutional factors contribute to the pursuit of one strategy over the other. We leverage institutional theory to examine how key organizational antecedents such as strategic orientation (mission), formal structure (size), and internal dynamics (patient case mix complexity) influence the rate at which organizations move toward or away from a single-sourcing configuration. Employing longitudinal modeling combined with sequence analysis techniques, we empirically evaluate IS sourcing strategies of nearly all U.S. hospitals operating continuously over a 9-year time frame from 2005 to 2013. We find that hospitals are generally trending toward a single-sourcing configuration and that formal structure and internal dynamics serve as predictors of this trend. Contrary to the predictions of institutional theory, we find that strategic orientation is not predictive of IS sourcing strategy. These results have important implications for research and practice. Notably, we are the first to quantify sourcing strategies, and, by doing so, are able to inform practitioners and academics of the key organizational characteristics that lead hospitals to move more quickly toward single-sourcing configurations.

Incorporating Comorbidity Within Risk Adjustment for UK Pediatric Cardiac Surgery

When considering early survival rates after pediatric cardiac surgery it is essential to adjust for risk linked to case complexity. An important but previously less well understood component of case mix complexity is comorbidity. The National Congenital Heart Disease Audit data representing all pediatric cardiac surgery procedures undertaken in the United Kingdom and Ireland between 2009 and 2014 was used to develop and test groupings for comorbidity and additional non-procedure-based risk factors within a risk adjustment model for 30-day mortality. A mixture of expert consensus based opinion and empiric statistical analyses were used to define and test the new comorbidity groups. The study dataset consisted of 21,838 pediatric cardiac surgical procedure episodes in 18,834 patients with 539 deaths (raw 30-day mortality rate, 2.5%). In addition to surgical procedure type, primary cardiac diagnosis, univentricular status, age, weight, procedure type (bypass, nonbypass, or hybrid), and era, the new risk factor groups of non-Down congenital anomalies, acquired comorbidities, increased severity of illness indicators (eg, preoperative mechanical ventilation or circulatory support) and additional cardiac risk factors (eg, heart muscle conditions and raised pulmonary arterial pressure) all independently increased the risk of operative mortality. In an era of low mortality rates across a wide range of operations, non-procedure-based risk factors form a vital element of risk adjustment and their presence leads to wide variations in the predicted risk of a given operation.