Using Operational Analysis to Improve Access to Pulmonary Function Testing

Background. Timely pulmonary function testing is crucial to improving diagnosis and treatment of pulmonary diseases. Perceptions of poor access at an academic pulmonary function laboratory prompted analysis of system demand and capacity to identify factors contributing to poor access. Methods. Surveys and interviews identified stakeholder perspectives on operational processes and access challenges. Retrospective data on testing demand and resource capacity was analyzed to understand utilization of testing resources. Results. Qualitative analysis demonstrated that stakeholder groups had discrepant views on access and capacity in the laboratory. Mean daily resource utilization was 0.64 (SD 0.15), with monthly average utilization consistently less than 0.75. Reserved testing slots for subspecialty clinics were poorly utilized, leaving many testing slots unfilled. When subspecialty demand exceeded number of reserved slots, there was sufficient capacity in the pulmonary function schedule to accommodate added demand. Findings were shared with stakeholders and influenced scheduling process improvements. Conclusion. This study highlights the importance of operational data to identify causes of poor access, guide system decision-making, and determine effects of improvement initiatives in a variety of healthcare settings. Importantly, simple operational analysis can help to improve efficiency of health systems with little or no added financial investment

Identifying Cases of Sleep Disorders through International Classification of Diseases (ICD) Codes in Administrative Data

Objectives Prevalence, and associated morbidity and mortality of chronic sleep disorders have been limited to small cohort studies, however, administrative data may be used to provide representation of larger population estimates of disease. With no guidelines to inform the identification of cases of sleep disorders in administrative data, the objective of this study was to develop and validate a set of ICD-codes used to define sleep disorders including narcolepsy, insomnia, and obstructive sleep apnea (OSA) in administrative data. Methods A cohort of adult patients, with medical records reviewed by two independent board-certified sleep physicians from a sleep clinic in Calgary, Alberta between January 1, 2009 and December 31, 2011, was used as the reference standard. We developed a general ICD-coded case definition for sleep disorders which included conditions of narcolepsy, insomnia, and OSA using: 1) physician claims data, 2) inpatient visit data, 3) emergency department (ED) and ambulatory care data. We linked the reference standard data and administrative data to examine the validity of different case definitions, calculating estimates of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).  Results From a total of 1186 patients from the sleep clinic, 1045 (88.1%) were classified as sleep disorder positive, with 606 (51.1%) diagnosed with OSA, 407 (34.4%) with insomnia, and 59 (5.0%) with narcolepsy. The most frequently used ICD-9 codes were general codes of 307.4 (Nonorganic sleep disorder, unspecified), 780.5 (unspecified sleep disturbance) and ICD-10 codes of G47.8 (other sleep disorders), G47.9 (sleep disorder, unspecified). The best definition for identifying a sleep disorder was an ICD code (from physician claims) 2 years prior and 1 year post sleep clinic visit: sensitivity 79.2%, specificity 28.4%, PPV 89.1%, and NPV 15.6%. ICD codes from ED/ambulatory care data provided similar diagnostic performance when at least 2 codes appeared in a time period of 2 years prior and 1 year post sleep clinic visit: sensitivity 71.9%, specificity 54.6%, PPV 92.1%, and NPV 20.8%. The inpatient data yielded poor results in all tested ICD code combinations. Conclusion Sleep disorders in administrative data can be identified mainly through physician claims data and with some being determined through outpatient/ambulatory care data ICD codes, however these are poorly coded within inpatient data sources. This may be a function of how sleep disorders are diagnosed and/or reported by physicians in inpatient and outpatient settings within medical records. Future work to optimize administrative data case definitions through data linkage are needed

Case report: Thrombosed giant cavernous carotid artery aneurysm secondary to cervical internal carotid artery dissection: An unusual entity

Spontaneous thrombosis of a giant intracranial aneurysm with parent artery occlusion is known. The exact mechanism is however unclear and various theories have been proposed. We present an unusual case of an angiographically documented cervical internal carotid artery (ICA) dissection, which led to total occlusion of the ICA distal to the dissected site, with acute cessation of forward blood flow. This resulted in acute upstream thrombosis of the giant cavernous carotid artery aneurysm and an acute cavernous sinus syndrome-like presentation

Use of Electronic Data and Existing Screening Tools to Identify Clinically Significant Obstructive Sleep Apnea

OBJECTIVES: To assess the ability of electronic health data and existing screening tools to identify clinically significant obstructive sleep apnea (OSA), as defined by symptomatic or severe OSA.METHODS: The present retrospective cohort study of 1041 patients referred for sleep diagnostic testing was undertaken at a tertiary sleep centre in Calgary, Alberta. A diagnosis of clinically significant OSA or an alternative sleep diagnosis was assigned to each patient through blinded independent chart review by two sleep physicians. Predictive variables were identified from online questionnaire data, and diagnostic algorithms were developed. The performance of electronically derived algorithms for identifying patients with clinically significant OSA was determined. Diagnostic performance of these algorithms was compared with versions of the STOP-Bang questionnaire and adjusted neck circumference score (ANC) derived from electronic data.RESULTS: Electronic questionnaire data were highly sensitive (>95%) at identifying clinically significant OSA, but not specific. Sleep diagnostic testing-determined respiratory disturbance index was very specific (specificity ≥95%) for clinically relevant disease, but not sensitive (ud_less_than35%). Derived algorithms had similar accuracy to the STOP-Bang or ANC, but required fewer questions and calculations.CONCLUSIONS: These data suggest that a two-step process using a small number of clinical variables (maximizing sensitivity) and objective diagnostic testing (maximizing specificity) is required to identify clinically significant OSA. When used in an online setting, simple algorithms can identify clinically relevant OSA with similar performance to existing decision rules such as the STOP-Bang or ANC.Peer Reviewe

Treatment of Sleep Disordered Breathing Liberates Obese Hypoxemic Patients from Oxygen.

Obese hypoxemic patients have a high prevalence of sleep disordered breathing (SDB). It is unclear to what extent treatment of SDB can improve daytime hypoxemia.We performed a retrospective cohort study of obese hypoxemic individuals, all of whom underwent polysomnography, arterial blood gas analysis, and subsequent initiation of positive airway pressure (PAP) therapy for SDB. Patients were followed for one year for change in partial pressure of arterial oxygen and the need for supplemental oxygen.One hundred and seventeen patients were treated with nocturnal PAP and had follow-up available. Adherence to PAP was satisfactory in 60%, and was associated with a significant improvement in daytime hypoxemia and hypercapnea; 56% of these patients were able to discontinue supplemental oxygen. Adherence to PAP therapy and the baseline severity of OSA predicted improvement in hypoxemia, but only adherence to PAP therapy predicted liberation from supplemental oxygen.The identification and treatment of SDB in obese hypoxemic patients improves daytime hypoxemia. It is important to identify SDB in these patients, since supplemental oxygen can frequently be discontinued following treatment with PAP therapy

Granulomatous Pneumocystis Jiroveci Pneumonia Associated with Immune Reconstituted HIV

Pneumocystis jiroveci pneumonia uncommonly presents with pulmonary nodules and granulomatous inflammation. An unusual case of granulomatous P jiroveci pneumonia in an HIV patient with a CD4+ lymphocyte count of greater than 200 cells/mm3, occurring in the context of immune reconstitution with highly active antiretroviral therapy, is described. The case highlights the importance of establishing this diagnosis to institute appropriate therapy.Peer Reviewe

Granulomatous Pneumocystis Jiroveci Pneumonia Associated with Immune Reconstituted HIV

Pneumocystis jiroveci pneumonia uncommonly presents with pulmonary nodules and granulomatous inflammation. An unusual case of granulomatous P jiroveci pneumonia in an HIV patient with a CD4+ lymphocyte count of greater than 200 cells/mm3, occurring in the context of immune reconstitution with highly active antiretroviral therapy, is described. The case highlights the importance of establishing this diagnosis to institute appropriate therapy

Using Operational Analysis to Improve Access to Pulmonary Function Testing

Background. Timely pulmonary function testing is crucial to improving diagnosis and treatment of pulmonary diseases. Perceptions of poor access at an academic pulmonary function laboratory prompted analysis of system demand and capacity to identify factors contributing to poor access. Methods. Surveys and interviews identified stakeholder perspectives on operational processes and access challenges. Retrospective data on testing demand and resource capacity was analyzed to understand utilization of testing resources. Results. Qualitative analysis demonstrated that stakeholder groups had discrepant views on access and capacity in the laboratory. Mean daily resource utilization was 0.64 (SD 0.15), with monthly average utilization consistently less than 0.75. Reserved testing slots for subspecialty clinics were poorly utilized, leaving many testing slots unfilled. When subspecialty demand exceeded number of reserved slots, there was sufficient capacity in the pulmonary function schedule to accommodate added demand. Findings were shared with stakeholders and influenced scheduling process improvements. Conclusion. This study highlights the importance of operational data to identify causes of poor access, guide system decision-making, and determine effects of improvement initiatives in a variety of healthcare settings. Importantly, simple operational analysis can help to improve efficiency of health systems with little or no added financial investment.Peer Reviewe