Risk Adjusting Health Care Provider Collaboration Networks.

OBJECTIVES: The quality of hospital discharge care and patient factors (health and sociodemographic) impact the rates of unplanned readmissions. This study aims to measure the effects of controlling for the patient factors when using readmission rates to quantify the weighted edges between health care providers in a collaboration network. This improved understanding may inform strategies to reduce hospital readmissions, and facilitate quality-improvement initiatives. METHODS: We extracted 4 years of patient, provider, and activity data related to cardiology discharge workflow. A Weibull model was developed to predict the risk of unplanned 30-day readmission. A provider-patient bipartite network was used to connect providers by shared patient encounters. We built collaboration networks and calculated the Shared Positive Outcome Ratio (SPOR) to quantify the relationship between providers by the relative rate of patient outcomes, using both risk-adjusted readmission rates and unadjusted readmission rates. The effect of risk adjustment on the calculation of the SPOR metric was quantified using a permutation test and descriptive statistics. RESULTS: Comparing the collaboration networks consisting of 2,359 provider pairs, we found that SPOR values with risk-adjusted outcomes are significantly different than unadjusted readmission as an outcome measure (p-value = 0.025). The two networks classified the same provider pairs as high-scoring 51.5% of the time, and the same low scoring provider pairs 85.6% of the time. The observed differences in patient demographics and disease characteristics between high-scoring and low-scoring provider pairs were reduced by applying the risk-adjusted model. The risk-adjusted model reduced the average variation across each individual's SPOR scored provider connections. CONCLUSIONS: Risk adjusting unplanned readmission in a collaboration network has an effect on SPOR-weighted edges, especially on classifying high-scoring SPOR provider pairs. The risk-adjusted model reduces the variance of providers' connections and balances shared patient characteristics between low- and high-scoring provider pairs. This indicates that the risk-adjusted SPOR edges better measure the impact of collaboration on readmissions by accounting for patients' risk of readmission.

Expectation versus Reality: The Impact of Utility on Emotional Outcomes after Returning Individualized Genetic Research Results in Pediatric Rare Disease Research, a Qualitative Interview Study.

PURPOSE: Much information on parental perspectives on the return of individual research results (IRR) in pediatric genomic research is based on hypothetical rather than actual IRR. Our aim was to understand how the expected utility to parents who received IRR on their child from a genetic research study compared to the actual utility of the IRR received. METHODS: We conducted individual telephone interviews with parents who received IRR on their child through participation in the Manton Center for Orphan Disease Research Gene Discovery Core (GDC) at Boston Children's Hospital (BCH). RESULTS: Five themes emerged around the utility that parents expected and actually received from IRR: predictability, management, family planning, finding answers, and helping science and/or families. Parents expressing negative or mixed emotions after IRR return were those who did not receive the utility they expected from the IRR. Conversely, parents who expressed positive emotions were those who received as much or greater utility than expected. CONCLUSIONS: Discrepancies between expected and actual utility of IRR affect the experiences of parents and families enrolled in genetic research studies. An informed consent process that fosters realistic expectations between researchers and participants may help to minimize any negative impact on parents and families.