Patients' lived experiences and recommendations for enhanced awareness and use of integrative oncology services in cancer care.

BACKGROUND: Consuming educational content, adhering to treatment plans and managing symptoms and side-effects can be overwhelming to new oncology patients. OBJECTIVE: The purpose of this study is to engage patients in conceptualization of enhanced clinic processes and digital health tools to support awareness and use of integrative oncology services. PATIENT INVOLVEMENT: We engaged patients in participatory design to understand lived experiences surrounding use of integrative oncology services during and after conventional cancer treatment. METHODS: Ten participatory design sessions were held with individual participants. Sessions began with patient story telling regarding diagnosis and paths to awareness and use of integrative oncology services. We then reviewed prototype mobile app screens to solicit feedback regarding digital health functionality to support patient navigation of symptom-alleviating options. RESULTS: Oncology patients are active participants in the management of symptoms and side effects. Patients who utilize yoga, acupuncture, and massage report a need for earlier patient education about these services. Patients express interest in digital health tools to match symptoms to options for relief, provide access to searchable information, and facilitate streamlined access to in-person and remote services. DISCUSSION: Patients co-produce wellbeing by seeking solutions to daily challenges and consuming educational content. Clinics can collaborate with patients to identify high priority needs and challenges. PRACTICAL VALUE: Active collaboration with patients is needed to identify unmet needs and guide development of clinic processes and digital health tools to enhance awareness and use of IO services in conventional cancer care. FUNDING: The principal investigator was supported by the U.S. Agency for Healthcare Research and Quality (AHRQ K12HS026370). The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of AHRQ. The sponsor had no role in the study design, data collection, analysis, report writing, or decision to submit for publication.

Evaluation of patient-level retrieval from electronic health record data for a cohort discovery task.

OBJECTIVE: Growing numbers of academic medical centers offer patient cohort discovery tools to their researchers, yet the performance of systems for this use case is not well understood. The objective of this research was to assess patient-level information retrieval methods using electronic health records for different types of cohort definition retrieval. MATERIALS AND METHODS: We developed a test collection consisting of about 100 000 patient records and 56 test topics that characterized patient cohort requests for various clinical studies. Automated information retrieval tasks using word-based approaches were performed, varying 4 different parameters for a total of 48 permutations, with performance measured using B-Pref. We subsequently created structured Boolean queries for the 56 topics for performance comparisons. In addition, we performed a more detailed analysis of 10 topics. RESULTS: The best-performing word-based automated query parameter settings achieved a mean B-Pref of 0.167 across all 56 topics. The way a topic was structured (topic representation) had the largest impact on performance. Performance not only varied widely across topics, but there was also a large variance in sensitivity to parameter settings across the topics. Structured queries generally performed better than automated queries on measures of recall and precision but were still not able to recall all relevant patients found by the automated queries. CONCLUSION: While word-based automated methods of cohort retrieval offer an attractive solution to the labor-intensive nature of this task currently used at many medical centers, we generally found suboptimal performance in those approaches, with better performance obtained from structured Boolean queries. Future work will focus on using the test collection to develop and evaluate new approaches to query structure, weighting algorithms, and application of semantic methods.

Natural Product Target Network Reveals Potential for Cancer Combination Therapies.

A body of research demonstrates examples of in vitro and in vivo synergy between natural products and anti-neoplastic drugs for some cancers. However, the underlying biological mechanisms are still elusive. To better understand biological entities targeted by natural products and therefore provide rational evidence for future novel combination therapies for cancer treatment, we assess the targetable space of natural products using public domain compound-target information. When considering pathways from the Reactome database targeted by natural products, we found an increase in coverage of 61% (725 pathways), relative to pathways covered by FDA approved cancer drugs collected in the Cancer Targetome, a resource for evidence-based drug-target interactions. Not only is the coverage of pathways targeted by compounds increased when we include natural products, but coverage of targets within those pathways is also increased. Furthermore, we examined the distribution of cancer driver genes across pathways to assess relevance of natural products to critical cancer therapeutic space. We found 24 pathways enriched for cancer drivers that had no available cancer drug interactions at a potentially clinically relevant binding affinity threshold of < 100nM that had at least one natural product interaction at that same binding threshold. Assessment of network context highlighted the fact that natural products show target family groupings both distinct from and in common with cancer drugs, strengthening the complementary potential for natural products in the cancer therapeutic space. In conclusion, our study provides a foundation for developing novel cancer treatment with the combination of drugs and natural products.

Naturopathic practice at north american academic institutions: description of 300,483 visits and comparison to conventional primary care.

This study collected patient visit data to explore similarities and differences between conventional and naturopathic primary care (PC). Administrative data from practice management software systems from the main teaching clinics of four of the eight accredited North American naturopathic academic institutions were abstracted into an integrated database containing five years (2006-2010) of visit, patient, laboratory, and prescribing data. Descriptive analyses of healthcare services were compared to the National Ambulatory Medical Care Survey (NAMCS). Over the five-year period, 300,483 patient visits to naturopathic doctors occurred at clinics, excluding visits at clinics operated by the schools in community settings. Patients were 69% female; mean age was 39 (SE 0.09). Older adults (>65) comprised 9% of the population and children (<16) comprised 8%. Comparing academic naturopathic clinics to national conventional PC (NAMCS), we found more patients paid out of pocket at naturopathic clinics (50 vs. 4%) and naturopathic clinics more frequently offered discounted care (26 vs. 0.3%). There was a 44% overlap in the most frequent 25 diagnoses for PC at conventional community clinics. Overall, these data suggest substantial similarities in care offered by academic naturopathic clinics, at which most Naturopathic Doctor (ND) students are trained, and by conventional PC practices.