Multidisciplinary Collaboration in the Treatment of Patients With Type 2 Diabetes in Primary Care: Analysis Using Process Mining

[EN] Background: Public health in several countries is characterized by a shortage of professionals and a lack of economic resources. Monitoring and redesigning processes can foster the success of health care institutions, enabling them to provide a quality service while simultaneously reducing costs. Process mining, a discipline that extracts knowledge from information system data to analyze operational processes, affords an opportunity to understand health care processes. Objective: Health care processes are highly flexible and multidisciplinary, and health care professionals are able to coordinate in a variety of different ways to treat a diagnosis. The aim of this work was to understand whether the ways in which professionals coordinate their work affect the clinical outcome of patients. Methods: This paper proposes a method based on the use of process mining to identify patterns of collaboration between physician, nurse, and dietitian in the treatment of patients with type 2 diabetes mellitus and to compare these patterns with the clinical evolution of the patients within the context of primary care. Clustering is used as part of the preprocessing of data to manage the variability, and then process mining is used to identify patterns that may arise. Results: The method is applied in three primary health care centers in Santiago, Chile. A total of seven collaboration patterns were identified, which differed primarily in terms of the number of disciplines present, the participation intensity of each discipline, and the referrals between disciplines. The pattern in which the three disciplines participated in the most equitable and comprehensive manner had a lower proportion of highly decompensated patients compared with those patterns in which the three disciplines participated in an unbalanced manner. Conclusions: By discovering which collaboration patterns lead to improved outcomes, health care centers can promote the most successful patterns among their professionals so as to improve the treatment of patients. Process mining techniques are useful for discovering those collaborations patterns in flexible and unstructured health care processes.This paper was partially funded by the National Commission for Scientific and Technological Research, the Formation of Advanced Human Capital Program and the National Fund for Scientific and Technological Development (CONICYT-PCHA/Doctorado Nacional/2016-21161705 and CONICYT-FONDECYT/1150365; Chile). The authors would like to thank Ancora UC primary health care centers for their help with this research. The founding sponsors had no role in the design of the study in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.Conca, T.; Saint Pierre, C.; Herskovic, V.; Sepulveda, M.; Capurro, D.; Prieto, F.; Fernández Llatas, C. (2018). Multidisciplinary Collaboration in the Treatment of Patients With Type 2 Diabetes in Primary Care: Analysis Using Process Mining. JOURNAL OF MEDICAL INTERNET RESEARCH. 20(4). https://doi.org/10.2196/jmir.8884S204Chen, C.-C., Tseng, C.-H., & Cheng, S.-H. (2013). Continuity of Care, Medication Adherence, and Health Care Outcomes Among Patients With Newly Diagnosed Type 2 Diabetes. Medical Care, 51(3), 231-237. doi:10.1097/mlr.0b013e31827da5b9International Diabetes FederationIDF20152018-03-19IDF Diabetes Atlas 7th Edition (2015) https://www.idf.org/e-library/epidemiology-research/diabetes-atlas/13-diabetes-atlas-seventh-edition.htmlMinisterio de Salud de Chileminsal.cl20102018-03-23Encuesta Nacional de Salud ENS Chile 2009-2010 http://www.minsal.cl/estudios_encuestas_salud/Ministerio de Salud de Chileminsal.cl20102018-03-20Guía Clinica Diabetes Mellitus Tipo 2 http://www.minsal.cl/portal/url/item/72213ed52c3e23d1e04001011f011398.pdfSapunar Z., J. (2016). EPIDEMIOLOGÍA DE LA DIABETES MELLITUS EN CHILE. Revista Médica Clínica Las Condes, 27(2), 146-151. doi:10.1016/j.rmclc.2016.04.003World Health Organizationwho.int2018-03-20Global Report on Diabetes http://www.who.int/diabetes/global-report/en/Poblete, F., Glasinovic, A., Sapag, J., Barticevic, N., Arenas, A., & Padilla, O. (2015). Apoyo social y salud cardiovascular: adaptación de una escala de apoyo social en pacientes hipertensos y diabéticos en la atención primaria chilena. Atención Primaria, 47(8), 523-531. doi:10.1016/j.aprim.2014.10.010Tuligenga, R. H., Dugravot, A., Tabák, A. G., Elbaz, A., Brunner, E. J., Kivimäki, M., & Singh-Manoux, A. (2014). Midlife type 2 diabetes and poor glycaemic control as risk factors for cognitive decline in early old age: a post-hoc analysis of the Whitehall II cohort study. The Lancet Diabetes & Endocrinology, 2(3), 228-235. doi:10.1016/s2213-8587(13)70192-xGamiochipi, M., Cruz, M., Kumate, J., & Wacher, N. H. (2016). Effect of an intensive metabolic control lifestyle intervention in type-2 diabetes patients. Patient Education and Counseling, 99(7), 1184-1189. doi:10.1016/j.pec.2016.01.017Wagner, E. H. (2001). Effect of Improved Glycemic Control on Health Care Costs and Utilization. JAMA, 285(2), 182. doi:10.1001/jama.285.2.182McDonald, J., Jayasuriya, R., & Harris, M. F. (2012). The influence of power dynamics and trust on multidisciplinary collaboration: a qualitative case study of type 2 diabetes mellitus. BMC Health Services Research, 12(1). doi:10.1186/1472-6963-12-63Gucciardi, E., Espin, S., Morganti, A., & Dorado, L. (2016). Exploring interprofessional collaboration during the integration of diabetes teams into primary care. BMC Family Practice, 17(1). doi:10.1186/s12875-016-0407-1Caron, F., Vanthienen, J., Vanhaecht, K., Limbergen, E. V., De Weerdt, J., & Baesens, B. (2014). Monitoring care processes in the gynecologic oncology department. Computers in Biology and Medicine, 44, 88-96. doi:10.1016/j.compbiomed.2013.10.015Rothman, A. A., & Wagner, E. H. (2003). Chronic Illness Management: What Is the Role of Primary Care? Annals of Internal Medicine, 138(3), 256. doi:10.7326/0003-4819-138-3-200302040-00034Organisation for Economic Co-operation and DevelopmentOECD20162018-03-20OECD Health Policy Overview: Health Policy in Chile http://www.oecd.org/els/health-systems/health-policy-in-your-country.htmRojas, E., Munoz-Gama, J., Sepúlveda, M., & Capurro, D. (2016). Process mining in healthcare: A literature review. Journal of Biomedical Informatics, 61, 224-236. doi:10.1016/j.jbi.2016.04.007Fernandez-Llatas, C., Lizondo, A., Monton, E., Benedi, J.-M., & Traver, V. (2015). Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems. Sensors, 15(12), 29821-29840. doi:10.3390/s151229769Mans, R. S., van der Aalst, W. M. P., & Vanwersch, R. J. B. (2015). Process Mining in Healthcare. SpringerBriefs in Business Process Management. doi:10.1007/978-3-319-16071-9Van der Aalst, W. M. P. (2011). Process Mining. doi:10.1007/978-3-642-19345-3Kim, E., Kim, S., Song, M., Kim, S., Yoo, D., Hwang, H., & Yoo, S. (2013). Discovery of Outpatient Care Process of a Tertiary University Hospital Using Process Mining. Healthcare Informatics Research, 19(1), 42. doi:10.4258/hir.2013.19.1.42Harper, P. R., Sayyad, M. G., de Senna, V., Shahani, A. K., Yajnik, C. S., & Shelgikar, K. M. (2003). A systems modelling approach for the prevention and treatment of diabetic retinopathy. European Journal of Operational Research, 150(1), 81-91. doi:10.1016/s0377-2217(02)00787-7Rebuge, Á., & Ferreira, D. R. (2012). Business process analysis in healthcare environments: A methodology based on process mining. Information Systems, 37(2), 99-116. doi:10.1016/j.is.2011.01.003Ferreira, D., Zacarias, M., Malheiros, M., & Ferreira, P. (2007). Approaching Process Mining with Sequence Clustering: Experiments and Findings. Business Process Management, 360-374. doi:10.1007/978-3-540-75183-0_26Cheong, L. H., Armour, C. L., & Bosnic-Anticevich, S. Z. (2013). Multidisciplinary collaboration in primary care: through the eyes of patients. Australian Journal of Primary Health, 19(3), 190. doi:10.1071/py12019Boyle, E., Saunders, R., & Drury, V. (2016). A qualitative study of patient experiences of Type 2 Diabetes care delivered comparatively by General Practice Nurses and Medical Practitioners. Journal of Clinical Nursing, 25(13-14), 1977-1986. doi:10.1111/jocn.13219UddinSHossainLEffects of Physician Collaboration Network on Hospital Outcomes2012Fifth Australasian Workshop on Health Informatics and Knowledge Management (HIKM 2012)2012Melbourne, AustraliaBorgermans, L., Goderis, G., Van Den Broeke, C., Verbeke, G., Carbonez, A., Ivanova, A., … Grol, R. (2009). Interdisciplinary diabetes care teams operating on the interface between primary and specialty care are associated with improved outcomes of care: findings from the Leuven Diabetes Project. BMC Health Services Research, 9(1). doi:10.1186/1472-6963-9-179Bosch, M., Dijkstra, R., Wensing, M., van der Weijden, T., & Grol, R. (2008). Organizational culture, team climate and diabetes care in small office-based practices. BMC Health Services Research, 8(1). doi:10.1186/1472-6963-8-180Counsell, S. R., Callahan, C. M., Clark, D. O., Tu, W., Buttar, A. B., Stump, T. E., & Ricketts, G. D. (2007). Geriatric Care Management for Low-Income Seniors. JAMA, 298(22), 2623. doi:10.1001/jama.298.22.2623Anderson, J. G. (2002). Evaluation in health informatics: social network analysis. Computers in Biology and Medicine, 32(3), 179-193. doi:10.1016/s0010-4825(02)00014-8Gray, J. E., Davis, D. A., Pursley, D. M., Smallcomb, J. E., Geva, A., & Chawla, N. V. (2010). Network Analysis of Team Structure in the Neonatal Intensive Care Unit. PEDIATRICS, 125(6), e1460-e1467. doi:10.1542/peds.2009-2621Mian, O., Koren, I., & Rukholm, E. (2012). Nurse practitioners in Ontario primary healthcare: Referral patterns and collaboration with other healthcare professionals. Journal of Interprofessional Care, 26(3), 232-239. doi:10.3109/13561820.2011.650300Crossley, N., Bellotti, E., Edwards, G., Everett, M. G., Koskinen, J., & Tranmer, M. (2015). Social Network Analysis for Ego-Nets. doi:10.4135/9781473911871Ministerio de Salud de Chile2018-03-20Fondo Nacional de Salud https://www.fonasa.cl/sites/fonasa/beneficiariosGoldstein, D. E., Little, R. R., Lorenz, R. A., Malone, J. I., Nathan, D., Peterson, C. M., & Sacks, D. B. (2004). Tests of Glycemia in Diabetes. Diabetes Care, 27(7), 1761-1773. doi:10.2337/diacare.27.7.1761Meduru, P., Helmer, D., Rajan, M., Tseng, C.-L., Pogach, L., & Sambamoorthi, U. (2007). Chronic Illness with Complexity: Implications for Performance Measurement of Optimal Glycemic Control. Journal of General Internal Medicine, 22(S3), 408-418. doi:10.1007/s11606-007-0310-5Vermeire, E., Hearnshaw, H., Van Royen, P., & Denekens, J. (2001). Patient adherence to treatment: three decades of research. A comprehensive review. Journal of Clinical Pharmacy and Therapeutics, 26(5), 331-342. doi:10.1046/j.1365-2710.2001.00363.xKarter, A. J., Parker, M. M., Moffet, H. H., Ahmed, A. T., Ferrara, A., Liu, J. Y., & Selby, J. V. (2004). Missed Appointments and Poor Glycemic Control. Medical Care, 42(2), 110-115. doi:10.1097/01.mlr.0000109023.64650.73World Health Organization20032018-03-20Adherence to long-term therapies: evidence for action http://www.who.int/chp/knowledge/publications/adherence_report/en/Toth, E. L., Majumdar, S. R., Guirguis, L. M., Lewanczuk, R. Z., Lee, T. K., & Johnson, J. A. (2003). Compliance with Clinical Practice Guidelines for Type 2 Diabetes in Rural Patients: Treatment Gaps and Opportunities for Improvement. Pharmacotherapy, 23(5), 659-665. doi:10.1592/phco.23.5.659.32203Melnikow, J., & Kiefe, C. (1994). Patient compliance and medical research. Journal of General Internal Medicine, 9(2), 96-105. doi:10.1007/bf02600211Fernandez-Llatas, C., Valdivieso, B., Traver, V., & Benedi, J. M. (2014). Using Process Mining for Automatic Support of Clinical Pathways Design. Data Mining in Clinical Medicine, 79-88. doi:10.1007/978-1-4939-1985-7_5Fernández-Llatas, C., Benedi, J.-M., García-Gómez, J., & Traver, V. (2013). Process Mining for Individualized Behavior Modeling Using Wireless Tracking in Nursing Homes. Sensors, 13(11), 15434-15451. doi:10.3390/s131115434Wishah, R. A., Al-Khawaldeh, O. A., & Albsoul, A. M. (2015). Impact of pharmaceutical care interventions on glycemic control and other health-related clinical outcomes in patients with type 2 diabetes: Randomized controlled trial. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 9(4), 271-276. doi:10.1016/j.dsx.2014.09.00

Factors affecting the survival of patients with oesophageal carcinoma under radiotherapy in the north of Iran

Factors relevant to the survival of patients with oesophageal cancer under radiotherapy have been studied in northern Iran where its incidence is high. We conducted an analytical study using a historical cohort and information from the medical charts of patients with oesophageal cancer. Out of 523 patients referred to the Shahid Rajaii radiotherapy centre in Babolsar from 1992 to 1996, we followed 230 patients for whom an address was available in 1998. The frequency of prognostic factors among those not contacted was very similar to those included in the study. The data were analysed using survival analysis by the nonparametric method of Kaplan Meier and the Cox regression model to determine risk ratios (RR) of prognostic factors. Survival rates were 42% at 1 year, 21% at 2 years, and 8% at 5 years after diagnosis. Patients aged 50–64 were found to have poorer survival compared with those less than 50 (RR = 1.73, P = 0.03); the risk ratio for ages f = 65 was 1.88 (P = 0.03). Females had significantly better survival than males (RR = 0.71, P = 0.02). For each 100 rads dose of radiotherapy, the risk ratio was significantly decreased by 1% (RR = 0.99, P = 0.05); for each session of radiotherapy, the risk ratio was significantly decreased by 4% (RR = 0.96, P = 0.0001); for each square centimetre size of surface under radiotherapy, the risk ratio significantly increased (RR = 1.002, P = 0.04). We did not observe a significant difference on survival by histology, anatomical location of tumours, or type of treatment (P > 0.05). Prognosis is extremely poor. © 2001 Cancer Research Campaign http://www.bjcancer.co

Safety and outcome of definitive chemoradiotherapy in elderly patients with oesophageal cancer

Little is known about chemoradiotherapy (CRT) in elderly patients with a locally advanced oesophageal cancer (OC). The aim of our study was to evaluate the tolerance and the outcome of elderly patients older than 70 years treated with CRT for a non-metastatic OC. Chemoradiotherapy was based on radiotherapy combined with a cisplatin-based chemotherapy. Clinical complete response (CCR) to CRT was evaluated on upper digestive endoscopy and computed tomography scan 6–8 weeks after CRT completion. One hundred and nine consecutive patients were included. A CCR was observed in 63 patients (57.8%) and 2-year survival was 35.5%. Adverse events ⩾grade 3 were observed in 26 (23.8%) patients. Chemotherapy dose reduction, chemotherapy delays more than 1 week, and treatment discontinuation were observed in 33 (30.3%), 45 (41.3%), and 17 patients (15.6%), respectively. Comorbidity index according to Charlson score was significantly associated with treatment tolerance. In multivariate analysis, a CCR to CRT (P<0.01), a dose of radiotherapy ⩾80% (P=0.02), and a Charlson score ⩽2 (P=0.046) were identified as independent prognostic factors of overall survival. These results suggest that CRT could be considered as an effective treatment without major toxicity in elderly patients with OC

Phase II study of bi-weekly administration of paclitaxel and cisplatin in patients with advanced oesophageal cancer

In a phase I study we demonstrated the feasibility of a bi-weekly combination of paclitaxel 180 mg m−2 with cisplatin 60 mg m−2. In this study we further assessed toxicity and efficacy of this schedule in the treatment of advanced cancer of the oesophagus or the gastro-oesophageal junction. Patients received paclitaxel 180 mg m−2 administered over 3 h followed by a 3-h infusion of cisplatin 60 mg m−2. Patients were retreated every 2 weeks unless granulocytes were <0.75×109 or platelets <75×109. Patients were evaluated after three and six cycles and responding patients received a maximum of eight cycles. Fifty-one patients were enrolled into the study. The median age was 56 years (range 32–78). WHO performance status were: 0 (19 patients); 1 (29 patients); 2 (three patients). All patients received at least three cycles of chemotherapy and all were evaluable for toxicity and response. Haematological toxicity consisted of uncomplicated neutropenia grade 3 in 39% and grade 4 in 31% of patients. Five patients (10%) were hospitalised, three patients because of treatment related complications and two patients because of infections without neutropenia. Sensory neurotoxicity was the predominant non-haematological toxicity; grade 1 and 2 neurotoxicity was observed in 43 and 20% of patients, respectively. Response evaluation in 51 patients with measurable disease: complete response 4%, partial response 39%, stable disease 43% and progressive disease in 14% of the patients. The median duration of response was 8 months. The median survival for all patients was 9 (range 2–29+) months and the one-year survival rate was 43%. Four patients who received additional local treatment (two patients surgery and two patients radiotherapy) are still disease free after a follow-up of 20–29 months. This bi-weekly treatment of paclitaxel and cisplatin is well tolerated by patients with advanced oesophageal cancer. The toxicity profile of this regimen compares favourable to that of previously used cisplatin- and paclitaxel-based regimens. Trials are underway evaluating this bi-weekly regimen in a neo-adjuvant setting

Neoadjuvant Chemoradiotherapy for Esophageal Cancer: A Review of Meta-Analyses

Background: Most randomized controlled trials (RCTs) that have compared neoadjuvant chemoradiation followed by surgery with surgery alone for locally advanced esophageal cancer have shown no difference in survival between the two treatments. Meta-analyses on neoadjuvant chemoradiation in esophageal cancer, however, are discordant. Methods: For the present study, published meta-analyses on neoadjuvant chemoradiation for esophageal cancer were identified from the PubMed database and critically appraised in order to make a judgment on the applicability of neoadjuvant chemoradiation in clinical practice and decision making. Results: Two of the six meta-analyses examined did not show a significant survival benefit in patients with resectable esophageal cancer. Differences in the studies included and statistical methods applied might account for this. Moreover, there was heterogeneity between the RCTs included in the meta-analyses with regard to the patients included, tumor histology, and radiotherapy and chemotherapy regimes. Also, surgical technique was not uniform. No data on individual patients were available for most meta-analyses. The RCTs included in the meta-analyses were of inadequate sample size. All were started in the nineties, and hence methods for diagnosis, staging, treatment delivery, and outcome measurement reflect clinical practice during that decade. Conclusions: The current data on neoadjuvant chemoradiation for esophageal cancer strongly indicate the need for designing future high-quality trials that will contribute to a better understanding of the role of neoadjuvant treatment for resectable cancer of the esophagus and help to identify patient subgroups that would benefit most

Induction cisplatin–irinotecan followed by concurrent cisplatin–irinotecan and radiotherapy without surgery in oesophageal cancer: multicenter phase II FFCD trial

A recent phase I study showed that weekly cisplatin, irinotecan and concurrent radiotherapy can be administered with moderate toxicity in patients with oesophageal cancer. Patients with no prior treatment and oesophageal cancer stage I to III, performance status <3, caloric intake >1500 kcal day−1 were included. Chemotherapy, with cisplatin 30 mg m−2 and irinotecan 60 mg m−2, was administered at days 1, 8, 22, 29, and concurrently with radiotherapy at days 43, 50, 64 and 71. Radiotherapy was delivered with 50 or 50.4 Gy in 25 fractions/5 weeks. Forty-three patients were included, 10 stage I, 19 stage II and 14 stage III. Mean age was 59.2 years (range 44–79). A total of 30 out of 43 (69.8%) patients underwent all planned treatment. During induction chemotherapy, 14 severe toxicities of grade 3 or 4 in 10 patients (23.3%) were reported with 57.1% due to haematoxicity. During chemoradiotherapy, 31 severe toxicities of grade 3 or 4 with 64.5% due to haematotoxicity were reported in 18 patients. One toxic death occurred (diarrhoea grade 4). The complete clinical response rate was 58.1% (95% CI: 43.4–72.8%). Overall survival rate at 1 and 2 years was 62.8%, (95% CI, 58.3–77.3%) and 27.9% (95% CI, 13.4–41.3%), respectively. In conclusion, cisplatin–irinotecan–radiotherapy is an active and well-tolerated regimen feasible in out-patients

Berberine Radiosensitizes Human Esophageal Cancer Cells by Downregulating Homologous Recombination Repair Protein RAD51

Esophageal squamous cell carcinomas (ESCC) have poor prognosis. While combined modality of chemotherapy and radiotherapy increases survival, most patients die within five years. Development of agents that confer cancer cell-specific chemo- and radiosensitivity may improve the therapy of ESCC. We here reported the discovery of berberine as a potent radiosensitizing agent on ESCC cells. by RNA interference similarly radiosensitized the cancer cells, and, conversely, introduction of exogenous RAD51 was able to significantly counteract the radiosensitizing effect of berberine, thus establishing RAD51 as a key determinant in radiation sensitivity. We also observed that RAD51 was commonly overexpressed in human ESCC tissues, suggesting that it is necessary to downregulate RAD51 to achieve high radio- or chemotherapeutic efficacy of ESCC in clinic, because overexpression of RAD51 is known to confer radio- and chemoresistance.Berberine can effectively downregulate RAD51 in conferring radiosensitivity on esophageal cancer cells. Its clinical application as an adjuvant in chemotherapy and radiotherapy of esophageal cancers should be explored