Quantifying the impact of customer allocations on supply chain performance

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; in conjunction with the Leaders for Global Operations Program at MIT, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 69-70).This project investigates the impact that customer allocations have on key cost and service indicators at Intel Corporation. Allocations provide a method to fill orders during constrained supply, when total demand for a given product exceeds available supply. It is hypothesized that allocations increase inventory levels since customers may not always take the supply that is reserved for them in allocations. Also, if the total number of allocation groupings could be reduced, it is thought that the total inventory needed to adequately service the same customer base could be reduced due to the increased potential for pooling. To test these hypotheses, historical data on allocations and product shipments were analyzed to assess how much inventory on hand could be attributed to using allocations. A model was built to calculate safety stock using historical allocations data as a demand indicator. Using this model, we simulate how much safety stock would be sufficient to meet expected demand as we reduce the number of allocations groups and pool risk across larger groups of customers. We also interview various supply managers to understand the impact allocations has on headcount, factoring in the geographical differences in managing allocations across a global supply chain. The results suggest that customer allocations are a complex yet necessary process at a large manufacturing firm. A moderate amount of extra inventory is carried since there is no penalty to customers for inflating forecasts, but relative to safety stock already kept on hand it is nominal. Strategically reducing allocations groupings in key product lines that are likely to be significantly constrained can provide a way to operate efficiently with less inventory on hand. Longer term, products can feasibly be taken off allocations when it is determined that supply is healthy enough to do so, but a robust process needs to be in place to handle this.by Neel Sheth.S.M.M.B.A

Phenytoin Interaction with Enteral Feedings Administered through Nasogastric Tubes

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142072/1/jpen0513.pd

Screening for caregiver psychosocial risk in children with medical complexity: A cross-sectional study

Objective To quantify psychosocial risk in family caregivers of children with medical complexity using the Psychosocial Assessment Tool (PAT) and to investigate potential contributing sociodemographic factors. Design Cross-sectional study. Setting Family caregivers completed questionnaires during long-term ventilation and complex care clinic visits at The Hospital for Sick Children, Toronto, Ontario, Canada. Patients A total of 136 family caregivers of children with medical complexity completed the PAT questionnaires from 30 June 2017 through 23 August 2017. Main outcome measures Mean PAT scores in family caregivers of children with medical complexity. Caregivers were stratified as \u27Universal\u27 low risk, \u27Targeted\u27 intermediate risk or \u27Clinical\u27 high risk. The effect of sociodemographic variables on overall PAT scores was also examined using multiple linear regression analysis. Comparisons with previous paediatric studies were made using T-test statistics. Results 136 (103 females (76%)) family caregivers completed the study. Mean PAT score was 1.17 (SD=0.74), indicative of \u27Targeted\u27 intermediate risk. Sixty-one (45%) caregivers were classified as Universal risk, 60 (44%) as Targeted risk and 15 (11%) as Clinical risk. Multiple linear regression analysis revealed an overall significant model (p=0.04); however, no particular sociodemographic factor was a significant predictor of total PAT scores. Conclusion Family caregivers of children with medical complexity report PAT scores among the highest of all previously studied paediatric populations. These caregivers experience significant psychosocial risk, demonstrated by larger proportions of caregivers in the highest-risk Clinical category

Using Electronic Health Records to Characterize Prescription Patterns: Focus on Antidepressants in Nonpsychiatric Outpatient Settings

Objective To characterize nonpsychiatric prescription patterns of antidepressants according to drug labels and evidence assessments (on-label, evidence-based, and off-label) using structured outpatient electronic health record (EHR) data. Methods A retrospective analysis was conducted using deidentified EHR data from an outpatient practice at a New York City-based academic medical center. Structured “medication–diagnosis” pairs for antidepressants from 35 325 patients between January 2010 and December 2015 were compared to the latest drug product labels and evidence assessments. Results Of 140 929 antidepressant prescriptions prescribed by primary care providers (PCPs) and nonpsychiatry specialists, 69% were characterized as “on-label/evidence-based uses.” Depression diagnoses were associated with 67 233 (48%) prescriptions in this study, while pain diagnoses were slightly less common (35%). Manual chart review of “off-label use” prescriptions revealed that on-label/evidence-based diagnoses of depression (39%), anxiety (25%), insomnia (13%), mood disorders (7%), and neuropathic pain (5%) were frequently cited as prescription indication despite lacking ICD-9/10 documentation. Conclusions The results indicate that antidepressants may be prescribed for off-label uses, by PCPs and nonpsychiatry specialists, less frequently than believed. This study also points to the fact that there are a number of off-label uses that are efficacious and widely accepted by expert clinical opinion but have not been included in drug compendia. Despite the fact that diagnosis codes in the outpatient setting are notoriously inaccurate, our approach demonstrates that the correct codes are often documented in a patient’s recent diagnosis history. Examining both structured and unstructured data will help to further validate findings. Routinely collected clinical data in EHRs can serve as an important resource for future studies in investigating prescribing behaviors in outpatient clinics

Nutrient Influences on Rat Intestinal Phenytoin Uptake

The intestinal uptake of phenytoin was studied as a function of concentration, intestinal region, coperfused glucose, and calcium chloride in rat intestinal perfusions and everted intestinal rings. Steady-state intestinal membrane permeabilities were obtained in an in situ perfusion system and initial rates of intestinal tissue uptake were obtained in an in vitro everted ring system as rate of absorption parameters. Steady-state membrane permeabilities were independent of phenytoin perfusion concentration and decreased from duodenum to ileum. Coperfusion of glucose increased, and high calcium chloride concentrations decreased phenytoin permeabilities. While phenytoin uptake in the in vitro ring system was also concentration-independent and depressed by high calcium concentrations, regional variations and glucose enhancement were not observed. Thus, drug–nutrient interactions involved in intestinal absorption from phenytoin solutions are a function of the isolation procedure.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41535/1/11095_2004_Article_305987.pd

Using Electronic Health Records to Characterize Prescription Patterns: Focus on Antidepressants in Nonpsychiatric Outpatient Settings

Objective To characterize nonpsychiatric prescription patterns of antidepressants according to drug labels and evidence assessments (on-label, evidence-based, and off-label) using structured outpatient electronic health record (EHR) data. Methods A retrospective analysis was conducted using deidentified EHR data from an outpatient practice at a New York City-based academic medical center. Structured “medication–diagnosis” pairs for antidepressants from 35 325 patients between January 2010 and December 2015 were compared to the latest drug product labels and evidence assessments. Results Of 140 929 antidepressant prescriptions prescribed by primary care providers (PCPs) and nonpsychiatry specialists, 69% were characterized as “on-label/evidence-based uses.” Depression diagnoses were associated with 67 233 (48%) prescriptions in this study, while pain diagnoses were slightly less common (35%). Manual chart review of “off-label use” prescriptions revealed that on-label/evidence-based diagnoses of depression (39%), anxiety (25%), insomnia (13%), mood disorders (7%), and neuropathic pain (5%) were frequently cited as prescription indication despite lacking ICD-9/10 documentation. Conclusions The results indicate that antidepressants may be prescribed for off-label uses, by PCPs and nonpsychiatry specialists, less frequently than believed. This study also points to the fact that there are a number of off-label uses that are efficacious and widely accepted by expert clinical opinion but have not been included in drug compendia. Despite the fact that diagnosis codes in the outpatient setting are notoriously inaccurate, our approach demonstrates that the correct codes are often documented in a patient’s recent diagnosis history. Examining both structured and unstructured data will help to further validate findings. Routinely collected clinical data in EHRs can serve as an important resource for future studies in investigating prescribing behaviors in outpatient clinics