"I wish they could be in my shoes": patients' insights into tertiary health care for type 2 diabetes mellitus.

BACKGROUND: Insightful accounts of patient experience within a health care system can be valuable for facilitating improvements in service delivery. OBJECTIVE: The aim of this study was to explore patients' perceptions and experiences regarding a tertiary hospital Diabetes and Endocrinology outpatient service for the management of type 2 diabetes mellitus (T2DM). METHOD: Nine patients participated in discovery interviews with an independent trained facilitator. Patients' stories were synthesized thematically using a constant comparative approach. RESULTS: Three major themes were identified from the patients' stories: 1) understanding T2DM and diabetes management with subthemes highlighting that specialist care is highly valued by patients who experience a significant burden of diabetes on daily life and who may have low health literacy and low self confidence; 2) relationships with practitioners were viewed critical and perceived lack of empathy impacted the effectiveness of care; and 3) impact of health care systems on service delivery with lack of continuity of care relating to the tertiary hospital model and limitations with appointment bookings negatively impacting on patient experience. DISCUSSION: The patients' stories suggest that the expectation of establishing a productive, ongoing relationship with practitioners is highly valued. Tertiary clinics for T2DM are well placed to incorporate novel technological approaches for monitoring and follow-up, which may overcome many of the perceived barriers of traditional service delivery. CONCLUSION: Investing in strategies that promote patient-practitioner relationships may enhance effectiveness of treatment for T2DM by meeting patient expectations of personalized care. Future changes in service delivery would benefit from incorporating patients as key stakeholders in service evaluation.

General Practitioners' perceptions of their role in cancer care and factors which influence this role.

Effective cancer care depends on inter-sectoral and inter-professional communication. General Practitioners (GPs) play a pivotal role in managing the health of most Australians, but their role in cancer care is unclear. This qualitative study explored GPs' views of this role and factors influencing their engagement with cancer care. Twelve metropolitan and non-metropolitan GPs in Queensland, Australia, were recruited between April and May 2008, and three focus groups and one interview were conducted using open-ended questions. The transcripts were analysed thematically. The first theme, GPs' perceptions of their role, comprised subthemes corresponding to four phases of the trajectory. The second theme, Enhancing GPs' involvement in ongoing cancer care, comprised subthemes regarding enhanced communication and clarification of roles and expectations. GPs' role in cancer care fluctuates between active advocacy during diagnosis and palliation, and ambivalent redundancy in between. The role is influenced by socioeconomic, clinical and geographical factors, patients' expectations and GPs' motivation. Not all participants wanted an enhanced role in cancer care, but all valued better specialist-GP communication. Role clarification is needed, together with greater mutual trust between GPs and specialists. Key needs included accessible competency training and mentoring for doctors unfamiliar with the system. Existing system barriers and workforce pressures in general practice must be addressed to improve the sharing of cancer care. Only one metropolitan focus group was conducted, so saturation of themes may not have been reached. The challenges of providing cancer care in busy metropolitan practices are multiplied in non-metropolitan settings with less accessible resources and where distance affects specialist communication. Non-metropolitan GPs learn from experience how to overcome referral and communication challenges. While the GPs identified solutions to their concerns, the role can be daunting. GPs are motivated to provide long-term care for their patients, but need to be acknowledged and supported by the health system.

Classification of pathology reports for cancer registry notifications.

OBJECTIVE: To develop a system for the automatic classification of pathology reports for Cancer Registry notifications. METHOD: A two pass approach is proposed to classify whether pathology reports are cancer notifiable or not. The first pass queries pathology HL7 messages for known report types that are received by the Queensland Cancer Registry (QCR), while the second pass aims to analyse the free text reports and identify those that are cancer notifiable. Cancer Registry business rules, natural language processing and symbolic reasoning using the SNOMED CT ontology were adopted in the system. RESULTS: The system was developed on a corpus of 500 histology and cytology reports (with 47% notifiable reports) and evaluated on an independent set of 479 reports (with 52% notifiable reports). RESULTS show that the system can reliably classify cancer notifiable reports with a sensitivity, specificity, and positive predicted value (PPV) of 0.99, 0.95, and 0.95, respectively for the development set, and 0.98, 0.96, and 0.96 for the evaluation set. High sensitivity can be achieved at a slight expense in specificity and PPV. CONCLUSION: The system demonstrates how medical free-text processing enables the classification of cancer notifiable pathology reports with high reliability for potential use by Cancer Registries and pathology laboratories.

Automatic extraction of cancer characteristics from free-text pathology reports for cancer notifications.

OBJECTIVE: To develop a system for the automatic classification of Cancer Registry notifications data from free-text pathology reports. METHOD: The underlying technology used for the extraction of cancer notification items is based on the symbolic rule-based classification methodology, whereby formal semantics are used to reason with the systematised nomenclature of medicine - clinical terms (SNOMED CT) concepts identified in the free text. Business rules for cancer notifications used by Cancer Registry coding staff were also incorporated with the aim to mimic Cancer Registry processes. RESULTS: The system was developed on a corpus of 239 histology and cytology reports (with 60% notifiable reports), and then evaluated on an independent set of 300 reports (with 20% notifiable reports). Results show that the system can reliably classify notifiable reports with 96% and 100% specificity, and achieve an overall accuracy of 82% and 74% for classifying notification items from notifiable reports at a unit record level from the development and evaluation set, respectively. CONCLUSION: Cancer Registries collect a multitude of data that requires manual review, slowing down the flow of information. Extracting and providing an automatically coded cancer pathology notification for review can lessen the reliance on expert clinical staff, improving the efficiency and availability of cancer information.

Symbolic rule-based classification of lung cancer stages from free-text pathology reports.

OBJECTIVE: To classify automatically lung tumor-node-metastases (TNM) cancer stages from free-text pathology reports using symbolic rule-based classification. DESIGN: By exploiting report substructure and the symbolic manipulation of systematized nomenclature of medicine-clinical terms (SNOMED CT) concepts in reports, statements in free text can be evaluated for relevance against factors relating to the staging guidelines. Post-coordinated SNOMED CT expressions based on templates were defined and populated by concepts in reports, and tested for subsumption by staging factors. The subsumption results were used to build logic according to the staging guidelines to calculate the TNM stage. MEASUREMENTS: The accuracy measure and confusion matrices were used to evaluate the TNM stages classified by the symbolic rule-based system. The system was evaluated against a database of multidisciplinary team staging decisions and a machine learning-based text classification system using support vector machines. RESULTS: Overall accuracy on a corpus of pathology reports for 718 lung cancer patients against a database of pathological TNM staging decisions were 72%, 78%, and 94% for T, N, and M staging, respectively. The system's performance was also comparable to support vector machine classification approaches. CONCLUSION: A system to classify lung TNM stages from free-text pathology reports was developed, and it was verified that the symbolic rule-based approach using SNOMED CT can be used for the extraction of key lung cancer characteristics from free-text reports. Future work will investigate the applicability of using the proposed methodology for extracting other cancer characteristics and types.

Effect of radiotherapy dose and volume on relapse in Merkel cell cancer of the skin.

PURPOSE: To assess the effect of radiotherapy (RT) dose and volume on relapse patterns in patients with Stage I-III Merkel cell carcinoma (MCC). PATIENTS AND METHODS: This was a retrospective analysis of 112 patients diagnosed with MCC between January 2000 and December 2005 and treated with curative-intent RT. RESULTS: Of the 112 evaluable patients, 88% had RT to the site of primary disease for gross (11%) or subclinical (78%) disease. Eighty-nine percent of patients had RT to the regional lymph nodes; in most cases (71%) this was for subclinical disease in the adjuvant or elective setting, whereas 21 patients (19%) were treated with RT to gross nodal disease. With a median follow-up of 3.7 years, the 2-year and 5-year overall survival rates were 72% and 53%, respectively, and the 2-year locoregional control rate was 75%. The in-field relapse rate was 3% for primary disease, and relapse was significantly lower for patients receiving >or=50 Gy (hazard ratio [HR] = 0.22; 95% confidence interval [CI], 0.06-0.86). Surgical margins did not affect the local relapse rate. The in-field relapse rate was 11% for RT to the nodes, with dose being significant for nodal gross disease (HR = 0.24; 95% CI, 0.07-0.87). Patients who did not receive elective nodal RT had a much higher rate of nodal relapse compared with those who did (HR = 6.03; 95% CI, 1.34-27.10). CONCLUSION: This study indicates a dose-response for subclinical and gross MCC. Doses of >or=50 Gy for subclinical disease and >or=55 Gy for gross disease should be considered. The draining nodal basin should be treated in all patients.