A Process Modelling Framework Based on Point Interval Temporal Logic with an Application to Modelling Patient Flows

This thesis considers an application of a temporal theory to describe and model the patient journey in the hospital accident and emergency (A&E) department. The aim is to introduce a generic but dynamic method applied to any setting, including healthcare. Constructing a consistent process model can be instrumental in streamlining healthcare issues. Current process modelling techniques used in healthcare such as flowcharts, unified modelling language activity diagram (UML AD), and business process modelling notation (BPMN) are intuitive and imprecise. They cannot fully capture the complexities of the types of activities and the full extent of temporal constraints to an extent where one could reason about the flows. Formal approaches such as Petri have also been reviewed to investigate their applicability to the healthcare domain to model processes. Additionally, to schedule patient flows, current modelling standards do not offer any formal mechanism, so healthcare relies on critical path method (CPM) and program evaluation review technique (PERT), that also have limitations, i.e. finish-start barrier. It is imperative to specify the temporal constraints between the start and/or end of a process, e.g., the beginning of a process A precedes the start (or end) of a process B. However, these approaches failed to provide us with a mechanism for handling these temporal situations. If provided, a formal representation can assist in effective knowledge representation and quality enhancement concerning a process. Also, it would help in uncovering complexities of a system and assist in modelling it in a consistent way which is not possible with the existing modelling techniques. The above issues are addressed in this thesis by proposing a framework that would provide a knowledge base to model patient flows for accurate representation based on point interval temporal logic (PITL) that treats point and interval as primitives. These objects would constitute the knowledge base for the formal description of a system. With the aid of the inference mechanism of the temporal theory presented here, exhaustive temporal constraints derived from the proposed axiomatic system’ components serves as a knowledge base. The proposed methodological framework would adopt a model-theoretic approach in which a theory is developed and considered as a model while the corresponding instance is considered as its application. Using this approach would assist in identifying core components of the system and their precise operation representing a real-life domain deemed suitable to the process modelling issues specified in this thesis. Thus, I have evaluated the modelling standards for their most-used terminologies and constructs to identify their key components. It will also assist in the generalisation of the critical terms (of process modelling standards) based on their ontology. A set of generalised terms proposed would serve as an enumeration of the theory and subsume the core modelling elements of the process modelling standards. The catalogue presents a knowledge base for the business and healthcare domains, and its components are formally defined (semantics). Furthermore, a resolution theorem-proof is used to show the structural features of the theory (model) to establish it is sound and complete. After establishing that the theory is sound and complete, the next step is to provide the instantiation of the theory. This is achieved by mapping the core components of the theory to their corresponding instances. Additionally, a formal graphical tool termed as point graph (PG) is used to visualise the cases of the proposed axiomatic system. PG facilitates in modelling, and scheduling patient flows and enables analysing existing models for possible inaccuracies and inconsistencies supported by a reasoning mechanism based on PITL. Following that, a transformation is developed to map the core modelling components of the standards into the extended PG (PG*) based on the semantics presented by the axiomatic system. A real-life case (from the King’s College hospital accident and emergency (A&E) department’s trauma patient pathway) is considered to validate the framework. It is divided into three patient flows to depict the journey of a patient with significant trauma, arriving at A&E, undergoing a procedure and subsequently discharged. Their staff relied upon the UML-AD and BPMN to model the patient flows. An evaluation of their representation is presented to show the shortfalls of the modelling standards to model patient flows. The last step is to model these patient flows using the developed approach, which is supported by enhanced reasoning and scheduling

Modeling and Optimizing Patient Flows

constructing a consistent process model and its simulation can be instrumental to be used in healthcare issues such as Consistent patient flow modeling. Current process modeling techniques used in healthcare are intuitive and imprecise such as flowcharts, unified modeling language activity diagram (UML AD) and business process modeling notation (BPMN). These techniques are vague in process description and cannot fully capture the complexities of the types of activities and types of temporal constraints between them. Additionally, to schedule patient flows; current modeling techniques does not offer any mechanism so healthcare relies on critical path method(CPM) and program evaluation review technique (PERT) that also have limitations i.e. finish-start barrier. It is imperative that temporal constraints between the start and/or end of a process needs to be specified, e.g., the start of A precedes the start (or end) of B, etc., however, these approaches failed to provide us with a mechanism for handling these temporal situations. This paper proposes a framework that provides enumeration of core concepts to describe a general knowledge base for Business and Healthcare domains. Algorithms are provided to represent the semantics of concepts i.e. based on their ontology. Furthermore, this logical basis is supported by Point graph (PG); a graphical tool, which has a formal translation to a point interval temporal logic (PITL) is used to simulate Patient flows for enhanced reasoning and correct representation. We will briefly evaluate an illustrative discharge patient flow example initially modeled using Unified Modeling Language Activity Diagram (UML AD) with the intention to compare with the technique presented here for its potential use to model patient flows

Modeling Patient Flows: A Temporal Logic Approach

Constructing a consistent process model can be instrumental in streamlining healthcare issues. Current process modeling techniques used in healthcare, such as flowcharts, unified modeling language activity diagram (UML AD), and business process modeling notation (BPMN) are intuitive and imprecise. These techniques are vague in process description and cannot fully capture the complexities of the types of activities and full extent of temporal constraints between them. Additionally, to schedule patient flows, current modeling techniques do not offer any mechanism, so healthcare relies on critical path method (CPM) and program evaluation review technique (PERT), that also have limitations i.e. finish-start barrier. It is imperative that temporal constraints between the start and/or end of a process needs to be specified, e.g., the start of A precedes the start (or end) of B, etc., however, these approaches failed to provide us with a mechanism for handling these temporal situations. This paper proposes a framework that provides enumeration of core terms/concepts to describe a general knowledge basis for Business and Healthcare domains. Definitions are provided to present the semantics of concepts i.e. based on their ontology. Furthermore, this logical basis is supported by Point graph (PG) notation; a graphical tool, which has a formal translation to a point interval temporal logic (PITL), and is used to model Patient flows suitable for enhanced reasoning and correct representation. We will evaluate an illustrative discharge patient flow example initially modeled using Unified Modeling Language Activity Diagram (UML AD) with the intention to compare with the technique presented here for its potential use to model patient flows

Q134R: Small Chemical Compound with NFAT Inhibitory Properties Improves Behavioral Performance and Synapse Function in Mouse Models of Amyloid Pathology

Inhibition of the protein phosphatase calcineurin (CN) ameliorates pathophysiologic and cognitive changes in aging rodents and mice with aging-related Alzheimer\u27s disease (AD)-like pathology. However, concerns over adverse effects have slowed the transition of common CN-inhibiting drugs to the clinic for the treatment of AD and AD-related disorders. Targeting substrates of CN, like the nuclear factor of activated T cells (NFATs), has been suggested as an alternative, safer approach to CN inhibitors. However, small chemical inhibitors of NFATs have only rarely been described. Here, we investigate a newly developed neuroprotective hydroxyquinoline derivative (Q134R) that suppresses NFAT signaling, without inhibiting CN activity. Q134R partially inhibited NFAT activity in primary rat astrocytes, but did not prevent CN-mediated dephosphorylation of a non-NFAT target, either in vivo, or in vitro. Acute (≤1 week) oral delivery of Q134R to APP/PS1 (12 months old) or wild-type mice (3–4 months old) infused with oligomeric Aβ peptides led to improved Y maze performance. Chronic (≥3 months) oral delivery of Q134R appeared to be safe, and, in fact, promoted survival in wild-type (WT) mice when given for many months beyond middle age. Finally, chronic delivery of Q134R to APP/PS1 mice during the early stages of amyloid pathology (i.e., between 6 and 9 months) tended to reduce signs of glial reactivity, prevented the upregulation of astrocytic NFAT4, and ameliorated deficits in synaptic strength and plasticity, without noticeably altering parenchymal Aβ plaque pathology. The results suggest that Q134R is a promising drug for treating AD and aging-related disorders

Transformation of UML Activity Diagram for Enhanced Reasoning

IT industry has adopted the unified modelling language activity diagram (UML-AD) as a de facto standard. UML AD facilitates modellers to graphically represent and document business processes to show the flow of activities and behaviour of a system. However, UML AD has many drawbacks such as lack of formal semantics i.e. ontology used for the constructs based on intuition, that vaguely describes processes and no provision for verifiability. Petri Net (PN) has been around for decades and used to model the workflow systems but PNs and its variants are too complex for business process modellers with no prior experience. A logical foundation is desirable to construct a business process with a precision that facilitates in transforming UML AD into a formal mechanism supported by verifiability capabilities for enhanced reasoning. Therefore, in this paper, we will provide a framework that will provide formal definitions for UML AD core terms and constructs used for modelling, and subsequently transform them to formal representation called point graph(PG). This will provide an insight into UML AD and will improve the overall functionality required from a modelling tool. A case study is conducted at King’s College Hospital trust’ to improve their patient flows of an accident and emergency (A&E) department

The epidemiology of suicide and attempted suicide in Dutch general practice 1983–2003

BACKGROUND: Many patients attempting or committing suicide consult their general practitioner (GP) in the preceding period, indicating that GPs might play an important role in prevention. The aim of the present study was to analyse the epidemiology of suicidal behaviour in Dutch General Practice in order to find possible clues for prevention. METHOD: Description of trends in suicide and suicide attempts occurring from 1983–2003 in the Dutch General Practice Sentinel Network, representing 1% of the Dutch population. The data were analysed with regard to: 1) suicidal behaviour trends and their association with household situation; 2) presence of depression, treatment of depression and referral rate by GPs; 3) contact with GP before suicide or suicide attempt and discussion of suicidal ideation. RESULTS: Between 1983 and 2003 the annual number of suicide and suicide attempts decreased by 50%. Sixty percent of the patients who committed or attempted suicide were diagnosed as depressed, of whom 91% were treated by their GP with an antidepressant. Living alone was a risk factor for suicide (odds ratio 1.99; 95% CI 1.50 to 2.64), whereas living in a household of 3 or more persons was a relative risk for a suicide attempt (odds ratio 1.81; 95% CI 1.34 to 2.46). Referral to a psychiatrist or other mental health professionals occurred in 65% of the cases. GPs recalled having discussed suicidal ideation in only 7% of the cases, and in retrospect estimated that they had foreseen suicide or suicide attempts in 31% and 22% of the cases, respectively, if there had been contact in the preceding month. CONCLUSION: With regard to the prescription of antidepressants and referral of suicidal patients to a psychiatrist, Dutch GPs fulfil their role as gatekeeper satisfactorily. However, since few patients discuss their suicidal ideation with their GP, there is room for improvement. GPs should take the lead to make this subject debatable. It may improve early recognition of depressed patients at risk and accelerate their referral to mental health professionals

Differential Effects of MYH9 and APOL1 Risk Variants on FRMD3 Association with Diabetic ESRD in African Americans

Single nucleotide polymorphisms (SNPs) in MYH9 and APOL1 on chromosome 22 (c22) are powerfully associated with non-diabetic end-stage renal disease (ESRD) in African Americans (AAs). Many AAs diagnosed with type 2 diabetic nephropathy (T2DN) have non-diabetic kidney disease, potentially masking detection of DN genes. Therefore, genome-wide association analyses were performed using the Affymetrix SNP Array 6.0 in 966 AA with T2DN and 1,032 non-diabetic, non-nephropathy (NDNN) controls, with and without adjustment for c22 nephropathy risk variants. No associations were seen between FRMD3 SNPs and T2DN before adjusting for c22 variants. However, logistic regression analysis revealed seven FRMD3 SNPs significantly interacting with MYH9—a finding replicated in 640 additional AA T2DN cases and 683 NDNN controls. Contrasting all 1,592 T2DN cases with all 1,671 NDNN controls, FRMD3 SNPs appeared to interact with the MYH9 E1 haplotype (e.g., rs942280 interaction p-value = 9.3E−7 additive; odds ratio [OR] 0.67). FRMD3 alleles were associated with increased risk of T2DN only in subjects lacking two MYH9 E1 risk haplotypes (rs942280 OR = 1.28), not in MYH9 E1 risk allele homozygotes (rs942280 OR = 0.80; homogeneity p-value = 4.3E−4). Effects were weaker stratifying on APOL1. FRMD3 SNPS were associated with T2DN, not type 2 diabetes per se, comparing AAs with T2DN to those with diabetes lacking nephropathy. T2DN-associated FRMD3 SNPs were detectable in AAs only after accounting for MYH9, with differential effects for APOL1. These analyses reveal a role for FRMD3 in AA T2DN susceptibility and accounting for c22 nephropathy risk variants can assist in detecting DN susceptibility genes

Utilisation of an operative difficulty grading scale for laparoscopic cholecystectomy

Background A reliable system for grading operative difficulty of laparoscopic cholecystectomy would standardise description of findings and reporting of outcomes. The aim of this study was to validate a difficulty grading system (Nassar scale), testing its applicability and consistency in two large prospective datasets. Methods Patient and disease-related variables and 30-day outcomes were identified in two prospective cholecystectomy databases: the multi-centre prospective cohort of 8820 patients from the recent CholeS Study and the single-surgeon series containing 4089 patients. Operative data and patient outcomes were correlated with Nassar operative difficultly scale, using Kendall’s tau for dichotomous variables, or Jonckheere–Terpstra tests for continuous variables. A ROC curve analysis was performed, to quantify the predictive accuracy of the scale for each outcome, with continuous outcomes dichotomised, prior to analysis. Results A higher operative difficulty grade was consistently associated with worse outcomes for the patients in both the reference and CholeS cohorts. The median length of stay increased from 0 to 4 days, and the 30-day complication rate from 7.6 to 24.4% as the difficulty grade increased from 1 to 4/5 (both p < 0.001). In the CholeS cohort, a higher difficulty grade was found to be most strongly associated with conversion to open and 30-day mortality (AUROC = 0.903, 0.822, respectively). On multivariable analysis, the Nassar operative difficultly scale was found to be a significant independent predictor of operative duration, conversion to open surgery, 30-day complications and 30-day reintervention (all p < 0.001). Conclusion We have shown that an operative difficulty scale can standardise the description of operative findings by multiple grades of surgeons to facilitate audit, training assessment and research. It provides a tool for reporting operative findings, disease severity and technical difficulty and can be utilised in future research to reliably compare outcomes according to case mix and intra-operative difficulty

Differentiation of the Lateral Compartment of the Cochlea Requires a Temporally Restricted FGF20 Signal

FGF20 signaling in mice is required specifically for the differentiation of cochlear outer hair cells, the cells most often damaged during age-related hearing loss