QUANTIFYING THE BURDEN OF DIABETES IN NOVA SCOTIA: TIME TO COMORBIDITY AND TIME TO DEATH FINAL REPORT 2010
Prepared by: Diabetes Care Program of Nova Scotia March 2010 Contact Information: Diabetes Care Program of Nova Scotia Suite 548 Bethune Building 1276 South Park Street Halifax, Nova Scotia, B3H 2Y9 Telephone: 902.473.3219 Fax: 902.473.3911 Email: dcpns@diabetescareprogram.ns.ca Website: www.diabetescareprogram.ns.ca
QUANTIFYING THE BURDEN OF DIABETES IN NOVA SCOTIA: TIME TO COMORBIDITY AND TIME TO DEATH FINAL REPORT 2010
Acknowledgements The Diabetes Care Program of Nova Scotia (DCPNS) would like to acknowledge and thank the many groups and individuals who were involved with this project. The quality of this work was enhanced through their invaluable feedback and insights. Cardiovascular Health Nova Scotia Diabetes Centre Managers and Educators Division of Endocrinology, Dalhousie University Department of Ophthalmology, Dalhousie University Nova Scotia Association of Optometrists Nova Scotia Diabetes Repository contributing partners Diabetes Care Program of Nova Scotia Nova Scotia Department of Health (NS DoH) Nova Scotia Pharmacare Program Reproductive Care Program of Nova Scotia Nova Scotia Renal Program Various clinical experts/external advisors We would also like to thank Jennifer Payne, Ian MacInnis, Zlatko Karlovic, and Pam Talbot for their hard work and dedication relating to this project. Finally, we would like to thank the Public Health Agency of Canada PHAC for the funding that made this important project possible. We also acknowledge the in-kind support of the DCPNS and NS DoH. Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 i
Glossary APLSF BP CIHI-DAD CRD CRF CVHNS CI DBP DC DCPNS DHA DoH DM Dx egfr GDM GP HCN HTN ICD-9-CM ICD-10-CA MSI NDSS NS NSDR PHAC PIA PreDM Pt RCMP RET Rx SBP Tx VA Annual Person-Level Summary File Blood pressure Canadian Institute for Health Information Discharge Abstract Database Chronic renal disease Chronic renal failure Cardiovascular Health Nova Scotia Confidence interval Diastolic blood pressure Diabetes Centre Diabetes Care Program of Nova Scotia District Health Authority Department of Health Diabetes mellitus Diagnosis Estimated glomerular filtration rate Gestational diabetes General Practitioner Health card number Hypertension International Statistical Classification of Diseases and Health Related Problems, Ninth Revision, Clinical Modification International Statistical Classification of Diseases and Health Related Problems, Tenth Revision, Canada Medical Services Insurance National Diabetes Surveillance System Nova Scotia Nova Scotia Diabetes Repository Public Health Agency of Canada Privacy Impact Assessment Prediabetes Patient Royal Canadian Mounted Police Retinopathy Prescription Systolic blood pressure Treatment Veterans Affairs ii Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Table of Contents Acknowledgements... i Glossary... ii Table of Contents... iii Chapter 1: Background...1 Introduction...1 Statement of Need...1 Rationale...2 Objectives...3 Chapter 2: Methodology...4 Advisory Group...4 Preliminary Indicator Development / Expert Consultation...4 Study Design...4 Data Sources...4 Data Linkage...6 Study Population...6 Study Measures...7 Statistical Analyses... 10 Test of the Provisional Nova Scotia Diabetes Repository... 11 Stakeholder Consultation... 11 Ethics... 12 Chapter 3: Results... 13 Preliminary Indicator Development / Expert Consultation... 13 Survival Analysis... 20 Sensitivity Analysis... 30 Test of the Provisional Nova Scotia Diabetes Repository... 36 Stakeholder Consultation... 37 Chapter 4: Discussion... 44 Key Learnings... 44 Next Steps... 46 References... 47 Appendices... 51 Appendix A: Physician Referral Form... 51 Appendix B: Patient Flow Sheet... 55 Appendix C: Diagnostic and Procedure Codes Used to Identify Comorbidity Cases... 61 Appendix D: DCPNS Triage Guidelines... 65 Appendix E: Deliverable 1: Interim Report Preliminary Indicators of Comorbidity... 69 Appendix F: Deliverable 1: Interim Report Progress to Date... 81 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 iii
iv Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Chapter 1: Background Introduction The Diabetes Care Program of Nova Scotia (DCPNS) is pleased to present this final report for the project titled Quantifying the Burden of Diabetes in Nova Scotia: Time to Comorbidity and Time to Death. The DCPNS and its many partners saw this project as an opportunity to gain a more complete appreciation of the burden of diabetes (DM) in the province by exploiting the rich data about clinically confirmed cases of DM housed in the DCPNS Registry. In Nova Scotia (NS), as with other provinces and jurisdictions, there is a dearth of information about the impact of developing DM earlier and living with DM longer. In the last decade, changes in diagnostic criteria for DM have resulted in the detection of DM cases earlier in the disease process. In addition, with more intensive management and aggressive attainment of targets, people with DM are living longer. Decision-makers need this information to inform strategies and to move providers into areas of programming better suited to help delay the onset of complications among high-risk populations and to address complex cases with multiple comorbidities. This work was a natural extension of initiatives already in place at the DCPNS. The DCPNS collects and analyses data from the DCPNS Registry and reports the finding back to Diabetes Centres (DCs), the District Health Authorities (DHAs), and the province. This project served to quantify the burden of DM using survival analysis methodology to describe time to comorbidities and time to death for a cohort of clinically confirmed cases of DM, to increase the quality and utility of data housed in the DCPNS Registry, and to compare the nature of the data collected by the DCPNS Registry and the National Diabetes Surveillance System (NDSS). This report provides a brief background to the project (Chapter 1), the methodology (Chapter 2) and results (Chapter 3), the learnings and next steps (Chapter 4). Supplemental materials are located in Appendices including the two interim reports submitted as Deliverable 1 and 2. Statement of Need Based on estimated prevalence using NDSS methodology, Nova Scotia has the second highest rate of DM in Canada, second only to Newfoundland and Labrador. [1] Although the incidence of DM did not increase significantly from 2001/02 to 2005/06, prevalence grew 19% from 7.3% to 8.7% among those 20 years. [2] In NS (2005/06), the standardized rate of comorbidities among those aged 20-40 years with DM (versus those without DM) was 12 times higher for cardiovascular disease; 25 times higher for hypertension (HTN), congestive heart failure, and nephropathy; 35 times higher for retinopathy (RET); and 65 times higher for non-traumatic lower extremity amputations. [2] As the average age of diagnosis declines and people live longer with their disease, the burden of DM will increase. There is a large body of epidemiological literature pertaining to the nature and course of DM; however, it remains difficult to ascertain the true burden of DM due to serious limitations with the data sources underlying this literature. Medical charts are both time consuming and expensive to retrieve and review, [3] and the quality and clarity of data may vary from one provider to the next. [4] Self-report data likely under-represent the burden of DM due to reporting bias [5-6] and provide only a snapshot in time Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 1
that is not useful for longitudinal surveillance of DM. Many Canadian studies about DM prognosis [2, 7-10] relies on administrative health records to ascertain DM cases. Cases of DM identified through administrative health records may not be clinically confirmed, and an unknown percentage are false positives. Other limitations associated with using administrative health records include incomplete ascertainment of DM and DM-related comorbidities due to coding practices, the inability to distinguish between the types of DM, and the lack of a true date of diagnosis for DM and DM-related comorbidities. The literature also lacks consensus about the concept of DM severity. Researchers with the Veterans Health Study developed a Diabetes Severity Measure based on the presence and progression of five DM-related complications: retinopathy, foot disease, autonomic and peripheral neuropathy, and atherosclerosis. [11] Canadian researchers examining the impact of DM on health-related quality of life defined DM severity in terms of DM treatment (i.e., diet alone, oral agents alone, insulin alone or in combination with oral agents), DM-specific emergency room visits in past six months, and DMspecific absenteeism from work in past six months. [12] Duration of DM, [13-16] age at onset, [13-14] A1C level, [13,17-19] and proteinuria [20] have also been used as markers for DM severity. Rationale Nova Scotia is unique in Canada in that the DCPNS maintains a population-based Registry of clinically confirmed cases of DM that permits the identification of exact date of DM diagnosis, comorbidities present at time of initial referral to a DC, approximate date of diagnosis for subsequent comorbidities, and date of death. Records from the DCPNS Registry can be linked at the person-level to administrative health records including those that form the basis for the NDSS. Recently, this data sharing and linkage process was streamlined through the successful development and pilot testing of a data transfer mechanism for the Nova Scotia Diabetes Repository (NSDR) a project funded through a Public Health Agency of Canada (PHAC) Enhanced Chronic Disease Surveillance Grant. The chief goal of this project was to enhance DM surveillance in NS through the development of the provisional NSDR and the accompanying data access and data security protocol. The construction and subsequent testing of the provisional NSDR demonstrated that provincial programs can effectively share data while protecting privacy. Together, these factors provide an unprecedented opportunity to explore the factors associated with survival for a large population-based cohort of clinically confirmed cases of DM. The DCPNS has partnered with Cardiovascular Health Nova Scotia (CVHNS), the Department of Ophthalmology at Dalhousie University, the NS Renal Program, several divisions within the NS Department of Health (DoH), and various clinical experts and external advisors to use survival analysis methodology to describe time to comorbidities and time to death for a cohort of clinically confirmed DM cases within the DCPNS Registry. 2 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Objectives 1. Examine time to comorbidity and time to death for a cohort of clinically confirmed DM cases from the DCPNS Registry using survival analysis methodology 2. Determine how sensitive the results from the survival analysis are to different definitions for date of DM diagnosis and date of onset for comorbidities 3. Evaluate utility of NSDR as a secure & timely data transfer mechanism 4. Disseminate the knowledge gained through this project to a broad audience of stakeholders Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 3
Chapter 2: Methodology Advisory Group During the first four months of the project (Dec/08 Mar/09), DCPNS engaged a broad range of stakeholders across multiple sectors as members of the project Advisory Group: CVHNS, Department of Ophthalmology at Dalhousie University, NS Association of Optometrists, NS Renal Program, and various clinical experts and external advisors. Literature Review / Expert Consultation Before any analytic work could begin, it was necessary to define a series of indicators for DM-related comorbidities. To this end, the DCPNS held a series of meetings with advisory group members to discuss the findings of a comprehensive review of information about indicators for DM-related comorbidities. A brief synthesis of the relevant information about indicators for DM-related comorbidities was prepared. For the purpose of this project, the comorbidities of interest were HTN, RET, and chronic renal disease (CRD). Study Design A population-based historical cohort of clinically confirmed DM cases from NS, Canada were followed prospectively from date of first visit at a DC until date of death or the end of the study period (March 31, 2009). Secondary analyses of data from the DCPNS Registry, alone and supplemented through individual-level linkage with administrative health records, were conducted in an effort to describe the population of DM cases and understand factors associated with survival. Data Sources DCPNS Registry The DCPNS Registry contains records for all new referrals to NS s DCs from April 1, 1994 onward. The DCPNS Registry is unique in Canada in that it contains records for over 75,000 clinically confirmed cases of DM and prediabetes (PreDM) across all ages throughout the province, including records for newly diagnosed paediatric cases of DM seen at DCs between 1992 and 1994. The DCPNS Registry includes data on patient demographics, DC visit information, and indicators of care. Demographic data are abstracted from a standardized Physician Referral Form (Appendix A). Sex, date of birth, and date of death are checked against the Medical Services Insurance (MSI) Registry file held by Medavie Blue Cross; reports of any suspected errors are sent to the originating DCs for correction. Data pertaining to DC encounters and indicators of care are abstracted from a standardized Patient Flow Sheet used by all DCs in the province (Appendix B). 4 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Administrative Health Records Canadian Institute for Health Information Discharge Abstract Database (CIHI-DAD) The NS DoH houses CIHI-DAD records from April 1, 1996 forward. The CIHI-DAD contains detailed information about all hospital admissions to Nova Scotia hospitals including administrative information, physician information, and patient demographics, diagnoses, procedures, and services. Data for the CIHI-DAD are abstracted by trained health record coders using a standardized data abstraction process. The CIHI uses support personnel, education programs, abstracting software, and data edits to improve the accuracy of their data. [21] The CIHI transfers year-to-date data to the NS DoH on a monthly basis. Medical Services Insurance Claims Medavie Blue Cross maintains the MSI Claims database on a server accessible by the NS DoH. The MSI Claims database contains claims data for health services rendered by physicians and other recognized healthcare providers (e.g., optometrist providing services to patients with DM) and reimbursed through Nova Scotia s MSI Program from January 1, 1996 forward. Data for the MSI Claims database are abstracted by the provider s clerical staff; these data include administrative information, physician information, costing, and patient demographics, diagnoses, and procedures. Physicians who are remunerated through alternative payment structures are encouraged to submit shadow billings claims to Medavie Blue Cross. Data contained in the MSI Claims are collected for claims adjudication by Medavie Blue Cross. This adjudication process filters out incorrect HCNs and double entries. Medavie Blue Cross also conducts random audits and chart reviews to ensure claims data are accurate. Medical Services Insurance Registry Medavie Blue Cross maintains the MSI Registry on a server accessible by the NS DoH. The MSI Registry is a longitudinal database with demographics and eligibility information about all registered beneficiaries (past and present) of the Nova Scotia MSI Program. The MSI registry does not capture records for Nova Scotians who have their healthcare costs covered through other programs such as the Canadian Armed Forces and the Royal Canadian Mounted Police (RCMP). Medavie Blue Cross updates the MSI Registry daily with incoming patient information. Data fields pertaining to an individual s address are updated yearly for Nova Scotia residents who are eligible for programs with a yearly renewal process (e.g., Seniors Pharmacare, Diabetes Assistance Program) and once every four years for all other MSI Program enrolees. The MSI Registry also received weekly updates from NS Vital Statistics about births and deaths. National Diabetes Surveillance System (NDSS) The NDSS collects nationally comparable data about DM using an administrative case definition based on hospital discharge abstracts (i.e., CIHI-DAD) and physician billings (e.g., MSI Claims) and collects prevalence information about DM-related comorbidities. With the exception of HTN, the comorbidity case definitions are based solely on hospital discharge abstracts. The case definition for HTN uses both hospital discharge abstracts and physician billings claims. Although all NDSS files used for Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 5
national reporting are aggregate in nature, each province holds their own Annual Person-Level Summary File (APLSF) that includes patient demographics and prevalent comorbidities for all cases identified as having DM. Data Linkage Nova Scotia is uniquely positioned within Canada to use survival analysis methodology to understand factors associated with survival among clinically confirmed DM cases. In NS, most healthcare services are covered through the publically funded single payer MSI program. Through this system, residents are issued a heath card number (HCN) that serves as a unique identifier across services. Using this HCN, longitudinal data about DM cases contained in the DPCNS Registry was deterministically linked at the individual level with the province s administrative health records. The data linkages were accomplished using the newly developed (2007/08), secure data access/sharing mechanism known as the provisional NSDR. The provisional NSDR was developed to streamline data access requests originating from within the NS DoH, including Provincial Programs (e.g., DCPNS). This mechanism was used to link DCPNS Registry records to CIHI-DAD and MSI Claims data and to link DCPNS Registry records to records for common cases found in the NDSS. The NSDR contains records for DM cases identified on or before March 31, 2006. Study Population Three cohorts were selected to complete objectives 1 and 2 of this study. Survival Analysis Cohort 1.1: DCPNS Registry Cohort The DCPNS Registry contains records for all attendees to NS DCs including members of the Canadian Armed Forces and RCMP as well as a limited number of out-of-province patients. The DCPNS Registry Cohort was restricted to NS residents with a valid NS HCN who were identified as having type 1 or type 2 DM on or before March 31, 2009 (see Figure 1). Members of the Canadian Armed Forces and RCMP (federal HCNs) were excluded as the mobile nature of these populations threatens to bias the outcome measure. Individuals identified as having PreDM, gestational diabetes (GDM), and/or other specific types of DM were excluded from the study cohort. Prediabetes is a risk factor for DM, but not a disease state. Gestational DM is a transient condition that usually resolves with parturition. The other specific types of DM are relatively rare metabolic conditions, many of which are caused by genetic mutations, drug use, or other disease processes. Cohort 1.2: DCPNS Registry Admin Cohort The DCPNS Registry Admin Cohort was comprised of a subset of cases from the DCPNS Registry Cohort that were present in the provisional NSDR (i.e., cases identified as having type 1 or type 2 DM on or before March 31, 2006). DCPNS Registry Cohort cases identified after March 31, 2006 were excluded as the NSDR was not updated with these cases (see Figure 1). 6 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Sensitivity Analysis Cohort 2.1: DCPNS Registry NDSS Cohort The DCPNS NDSS Cohort was comprised of a subset of cases from the DCPNS Registry Cohort that were present in the provisional NSDR (i.e., cases identified as having type 1 or type 2 DM on or before March 31, 2006) and had a matching record in the NDSS (see Figure 1). DCPNS Registry Cohort cases identified after March 31, 2006 were excluded as the NSDR was not updated with these cases. Figure 1: Study Cohorts Study Measures Survival Analysis A variety of study measures will be constructed, tested, and refined: outcome variables are presented in Table 1 and explanatory variables are presented in Table 2. Table 1: Variable Outcome variables for survival analysis Description Vital Status If a date of death was present in the DCPNS Registry, the record was assigned a Vital Status = 1, otherwise Vital Status = 0 Cohort 1.1: 1 = deceased as of March 31, 2009 0 = assumed to be alive as of March 31, 2009 Cohort 1.2: 1 = deceased as of March 31, 2006 0 = assumed to be alive as of March 31, 2006 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 7
Variable Survival Time Description Date of death or date of censor from the DCPNS Registry minus Date of diagnosis (Dx) from the DCPNS Registry Cohort 1.1: March 31, 2009 for cases with no recorded date of death Cohort 1.2: March 31, 2006 for cases with no recorded date of death Table 2: Variable Age at DM diagnosis a Age at first DC visit a Sex a DHA a Explanatory variables for survival analysis Description Date of DM Dx from the DCPNS Registry minus Date of birth from the DCPNS Registry Date of first DC visit from the DCPNS Registry minus Date of birth from the DCPNS Registry Sex from the DCPNS Registry DHA of first DC visited from the DCPNS Registry HTN Status If an indicator of HTN was present, the record was assigned an HTN Status = 1, otherwise HTN Status = 0 Cohort 1.1: HTN Status = 1 if a patient had 1 record in the DCPNS Registry indicating a medical problem of HTN, an antihypertensive medication, and/or a blood pressure (BP) 140/90 Cohort 1.2: HTN Status = 1 if a patient had 1 record in the DCPNS Registry indicating a medical problem of HTN, an antihypertensive medication, and/or a BP 140/90 and/or 1 record with an ICD-9-CM / ICD- 10-CA code for HTN b in either the CIHI-DAD or MSI Claims database RET Status If an indicator of RET was present, the record was assigned a RET Status = 1, otherwise RET Status = 0 Cohort 1.1: RET Status = 1 if a patient had 1 record in the DCPNS Registry indicating a medical problem of RET Cohort 1.2: RET Status = 1 if a patient had 1 record in the DCPNS Registry indicating a medical problem of RET and/or 1 record with an ICD-9-CM / ICD-10-CA code for RET b in either the CIHI-DAD or MSI Claims database a b Same for Cohort 1 and Cohort 2 See Appendix C for ICD-9-CM and ICD-10-CA codes 8 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Variable Description CRD Status If an indicator of CRD was present, the record was assigned a CRD Status = 1, otherwise CRD Status = 0 Cohort 1.1: CRD Status = 1 if a patient had 1 record in the DCPNS Registry indicating a medical problem of CRD and/or an estimated glomerular filtration rate (egfr) < 60mL/min/1.73m 2 Cohort 1.2: CRD Status = 1 if a patient had 1 record in the DCPNS Registry indicating a medical problem of CRDF and/or an (egfr) < 60mL/min/1.73m 2 and/or 1 record with an ICD-9-CM / ICD-10-CA code for CRD b in either the CIHI-DAD or MSI Claims database Objective 2: Sensitivity Analysis Pairs of study measures were constructed to determine how sensitive the results of the survival analysis were to date of diagnosis and presence of HTN: outcome variables are presented in Table 3 and explanatory variables are presented in Table 4. Table 3: Variable Outcome variables for sensitivity analysis Description DCPNS Registry DCPNS Vital Status DCPNS Survival Time If a date of death was present in the DCPNS Registry, the record was assigned a DCPNS Vital Status = 1, otherwise DCPNS Vital Status = 0 1 = deceased as of March 31, 2006 0 = assumed to be alive as of March 31, 2006 Date of death or date of censor in the DCPNS Registry minus Date of Dx in DCPNS Registry Date of censor = March 31, 2006 for cases with no recorded date of death in DCPNS Registry NDSS NDSS Vital Status NDSS Survival Time If a date of death was present in the NDSS, the record was assigned an NDSS Vital Status = 1, otherwise NDSS Vital Status = 0 1 = deceased as of March 31, 2006 0 = assumed to be alive as of March 31, 2006 Date of death or date of censor in NDSS minus Date of Dx in NDSS Date of censor = March 31, 2006 for cases with no recorded date of death in NDSS Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 9
Table 4: Variable Explanatory variables for sensitivity analysis Description DCPNS Registry DCPNS age at DM diagnosis Sex DCPNS HTN Status Date of DM Dx in the DCPNS Registry minus Date of birth in the DCPNS Registry Sex from DCPNS Registry If an indicator of HTN was present, the record was assigned a DCPNS HTN Status = 1, otherwise DCPNS HTN Status = 0 DCPNS HTN Status = 1 if a patient had 1 record in the DCPNS Registry indicating a medical problem of HTN, an antihypertensive medication, and/or a BP 140/90 NDSS NDSS age at DM diagnosis Sex NDSS HTN Status Date of DM Dx in the NDSS Date of birth c in the DCPNS Registry Sex c from DCPNS Registry If an indicator of HTN was present, the record was assigned an NDSS HTN Status = 1, otherwise NDSS HTN Status = 0 NDSS HTN Status = 1 if a patient had 1 record of HTN in the NDSS d Statistical Analyses All statistical analyses were conducted using SPSS v15. Objective 1: Survival Analysis Descriptive statistics were computed to describe cases of DM in terms of sex, DHA, age at DM Dx, age at referral to a DC, survival time, and presence of comorbidities using the DCPNS Registry alone and supplemented by data in the CIHI-DAD and MSI Claims database. To explore whether survival differed based on demographic and clinical factors, Cox proportional hazard models were constructed to quantify differences in survival by DM type, sex, and the presence of HTN, CRD, and RET. All models were adjusted for age at DM Dx, age at first DC visit, and DHA. Age at DM Dx is inherently related to survival the later in life individuals are diagnosed with DM, the less opportunity they have for survival. The lag between DM Dx and first DC visit also can impact survival; age at first DC visit was used to control for this potential confounder. Finally, DC referral patterns often vary from one DHA to another. For example, re-referral of previously diagnosed DM c d DCPNS verifies patient s date of birth and sex against the MSI Registry, the same source used for the NDSS; for these two variables, the information in the DCPNS Registry and NDSS is identical. The NDSS case definition for HTN is 2 physician claims or 1 hospitalization within two years with an ICD-9-CM / ICD-10-CA code for HTN [22] 10 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
cases occurs more often in one DHA due to their patient discharge policy (i.e., patients are automatically discharged after 1-2 years); the remaining eight DHAs do not discharge patients. Given the large sample sizes and exploratory nature of the analyses, all results are presented pictorially without reporting specific p-values and hazard rate ratios. Objective 2: Sensitivity Analysis Descriptive statistics were computed to describe differences between DCPNS Registry and NDSS in terms of date of Dx, age at DM Dx, HTN status, and survival. A sensitivity analysis was conducted to determine whether different case definitions for date of DM Dx (DCPNS vs NDSS) and presence of HTN (DCPNS vs NDSS) affected results. Kaplan Meier curves and Cox proportion hazard models were constructed using DCPNS Registry data and using NDSS data, and the results were compared. Test of the Provisional Nova Scotia Diabetes Repository This project represented the first real world data linkage scenario that could be used to evaluate the utility of the provisional NSDR as a secure and timely data transfer mechanism. The time required to access data from the DCPNS Registry, CIHI-DAD, MSI Claims, MSI Registry, and the NDSS was tracked from submission of the Application for Access to Provisional NSDR Data until receipt of the requisite datasets. The time required to receive security clearance for the project manager and project analyst was also tracked. Stakeholder Consultation The analysis phase of the project was delayed due to difficulties receiving approval for an amendment to the Privacy Impact Assessment (PIA) for the NSDR; the PIA was submitted to the NS DoH in February 2009 with verbal confirmation of approval being granted in September 2009 and written approval being granted in November 2009. As such, there was insufficient time to consult with the project Advisory Group regarding the results of the survival analysis and sensitivity analysis before preparing this final report. In lieu of discussing the final results with interested stakeholders and obtaining their input with regard to the reporting and presentation of this, and similar data, in future DCPNS Reports, DCPNS held a series of semi-structured focus groups with the Division of Endocrinology (1 session), DC educators (4 sessions), and DC managers (1 session). The goals of these sessions were as follows: Share some preliminary findings from the project Understand how these experts interpret the term DM severity Assess specific data elements required to fully profile DM patient s health status Assess how data about DM patient s health status should be disseminated The DCPNS Coordinator invited all members of the Division of Endocrinology at Dalhousie University to participate in a 90-minute face-to-face focus group held as part of the Division s monthly meeting. The DCPNS Coordinator also invited all DM educators (nurses and dietitians) working at the Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 11
province s 39 DCs to participate in a 90-minute teleconference focus group and all DC Managers representing the province s 9 DHAs to participate in a 60-minute teleconference focus group. At least one week prior to each focus group session, participants received a 2-page document with the questions to be addressed during the session. Participants were asked to review the questions in advance of their session. Participants were systematically assigned to answer questions in a specific order so that each participant had an opportunity to respond first, second, third, etc. All focus groups were facilitated by the DCPNS Coordinator. Diabetes Centre educators and managers were given a modest honorarium. Ethics This study was conducted as part of quality assurance activities performed by the DCPNS; as such, ethics approval was not required. Funding for this project was provided in part through a grant from the PHAC. The PHAC had no role in the execution, analysis, and interpretation of this study. 12 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Chapter 3: Results Preliminary Indicator Development / Expert Consultation Measures for indicators of comorbidity can be derived from two different types of data: patient charts and administrative records. Measures Derived from Patient Charts Ideal measures for indicators of comorbidity are based on actual anthropometric measurements such as height, weight, blood glucose levels, blood pressure, and creatinine clearance to name a few. In Canada, these measures are recorded in patient charts maintained by physicians. Some measures such as blood chemistry profiles also may be found in separate databases maintained by biomedical laboratories. Patient charts provide a rich historical account of a person s encounters with the healthcare system; however, they often are both time consuming and expensive to retrieve and review. Clinical Registries generally are comprised of information from existing sources like patient charts, electronic medical records, and referral forms, making them more feasible to use for the purpose of indicator development. The information contained in this type of registry tends to be variable across jurisdictions; thus, indicators developed using these data sources may not be comparable to those used in other areas. In NS, the DCPNS Registry includes records for all new referrals to the provinces DCs since April 1, 1994. As of March 2009, this Registry contained information for more than 75,000 individuals diagnosed with DM or PreDM. Registry data are routinely analysed and interpreted by the DCPNS, and the results are shared with DCs, DHAs, and the province through annual reports. Knowledge gained from these reports informs business planning, program evaluation, benchmarking, and the development of targeted interventions. Measures Derived from Administrative Data Measures for indicators of comorbidity based on administrative data can vary along several dimensions including data source, diagnostic codes, number of events, and number of years during which the event can occur. In Canada, three main types of administrative data are used for constructing these measures: the CIHI-DAD, physician billings claims, and pharmacy claims. Indicators derived from administrative data are very useful for generating nationally comparable statistics as most provinces and territories can readily link information from some or all of the data sources listed above. The NDSS is an excellent example of how administrative data are used to generate nationally comparable statistics pertaining to chronic disease. The NDSS was established in 2001 to address a critical gap in knowledge about the burden of DM across Canada. The case definition for the NDSS is based on routinely collected data housed in the CIHI-DAD and physician billings records available in all provinces and territories. More recent work has focussed on expanding the surveillance capacity of the NDSS to encompass measures of DM-related comorbidities. Until recently, NDSS estimates of comorbidities were limited to annual prevalence figures derived solely from hospital data (i.e., CIHI- DAD) and truly underestimated the burden of DM-related comorbidities, especially for comorbidities Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 13
commonly diagnosed and treated within the context of a physician s office (e.g., HTN, dyslipidemia). The newest version of the NDSS v209 [22] has expanded the case definition for HTN to include data from physician billings claims. Indicators of Comorbidity The following section describes indicators of comorbidity being used by the DCPNS and NDSS as well as the relevant information about indicators for DM-related comorbidities found in the literature. A brief definition for each indicator of comorbidity is followed by a list of measures used by the DCPNS, the NDSS, and select measures reported in literature within the last ten years. Hypertension Hypertension is a condition marked by elevated systolic BP (SBP > 140 mmhg) or diastolic BP (DBP > 90 mmhg) or both. This condition is a very common comorbidity of DM and a potent risk factor for DM-related micro- and macro-vascular disease. The DCPNS Registry contains several data fields that can be used independently or in combination to identify HTN cases: physician diagnosis of HTN at time of referral, use of antihypertensive medications at time of DC visit, and BP at time of DC visit. The NDSS [22] has just expanded its case definition for HTN to include information from physician billings claims. Previously, their HTN definition was based solely on data from the CIHI-DAD. Finally, there is a plethora of literature detailing how data from patient charts and/or administrative health records can be used to identify cases of HTN. Table 5 displays the data source and HTN measures for a sampling of this literature. Table 5: Literature documenting the measurement of hypertension Citation Location Data Source Indicator Measurement Patient Chart Data DCPNS Registry Nova Scotia, Canada Patient chart, physician referral form Physician Dx, 1 SBP > 140 mmhg and/or DSP > 90 mmhg, and/or use of an antihypertensive medication Mubarak et al., 2008 [23] Amman, Jordan Chart abstraction and structured interview For DM cases, an average of 2 SBP 130 mmhg or DBP 80 mmhg or use of an antihypertensive medication Petrella et al., Southwestern 2008 [24] Ontario, Canada Chart-abstracted medical records database Physician Dx, 2 BP > 140/90 mmhg (or > 130/80 for DM cases), or 1 prescription (Rx) for an antihypertensive medication Sturkenboom et al., 2008 [25] Netherlands & Italy Computer-based patient record General practitioner (GP) or specialist Dx of HTN, 2 BP measurements 140/90 mmhg, or 1 Rx for an antihypertensive medication 14 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Citation Location Data Source Indicator Measurement Turner et al., Pennsylvania, 2008 [26] United States Electronic Medical Record Physician Dx with an ICD-9 code of 401.xx-404.xx and use of an antihypertensive medication, physician Dx with an ICD-9 code of 401.xx- 404.xx and elevated BP, or elevated BP at 2 visits Elevated BP: 130 mmhg or DBP 80 mmhg for patient (Pt) with DM or chronic renal failure (CRF) or 140 mmhg or DBP 80 mmhg for Pt without DM Hicks et al., United States Electronic 2005 [27] Medical Record 2 clinic visit with a primary or secondary Dx with an ICD-9 code of 401-401.9 or 405-405.99 Russell et al., Nova Scotia, 2005 [28] Canada Administrative Data DCPNS Registry Use of antihypertensive medication or average SBP and/or DBP above guideline cut-point NDSS Canada Physician v209 [22] Billings Claims & CIHI-DAD 2 physicians claims or 1 hospitalization in 2 years with an ICD-9-CM code of 401-405 or an ICD-10-CA of I10-I13, I15 McDonald et al., 2008 [29] British Columbia, Canada Physician Billings Claims and CIHI-DAD Evaluated 12 combinations: 2 physicians claims or 1 hospitalization in 1, 2, or 3 years (first & last date rule) 2 physicians claims in 1, 2, or 3 years (first & last date rule) Tu et al., Ontario, Canada Physician 2008 [30] Billings Claims and CIHI-DAD Wiréhn et al., Sweden Administrative 2007 [31] healthcare register Bullano et United States Administrative al., 2006 [32] claims database 2 physician claims or 1 hospitalization with an ICD-9 code of 401.x 405.x or ICD-10 code of I10.x I15.x 1 Dx for contact with healthcare services with an ICD-10 code of I10- I13 or I15 Evaluated multiple combination: 1 ( 2 or 3) medical claim(s) Dx with an ICD-9-CM code of 401.xx 1 (or 2, or 3) medical claim(s) Dx with an ICD-9-CM code of 401.xx and 1 (or 2) Rx for an antihypertensive medication Barron et al., Southwestern & 2004 [33] Western United States Administrative claims database 1 claim with an ICD-9 code of 401.xx 404.xx and 1 Rx for an antihypertensive medication Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 15
Citation Location Data Source Indicator Measurement Borzecki et al., 2004 [34] United States National Veterans Affairs (VA) administrative database 1 Dx with an ICD-9-CM code of 401, 402, or 405 in 1 year Rector et al., Midwestern & 2004 [35] Northeastern United States Lund et al., Iowa, United 2001 [36] States Physician, facility, and pharmacy claims Medical claims Evaluated 38 combinations involving a Dx with an ICD-9-CM code of 401.0, 401.1, 401.9, 402.xx, 403.xx, 404.xx and/or 1 Rx for an antihypertensive medication 1 or 2 claims with a Dx in 1 or 2 years, 1 or 2 face-to-face claims with a Dx in 1 or 2 years, 1 or 2 face-to-face claims with a primary Dx in 1 or 2 years Combinations above plus or a Rx Combinations above plus and a Rx to above 1 Rx claim in 1 or 2 years ICD-9 code of 401.xx 405.xx 16 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Retinopathy Retinopathy is a condition marked by damage to the blood vessels that supply the retina. At first, the blood vessels leak fluid or blood causing retinal edema (background RET). As the disease progresses, the blood vessels become blocked and the retina dies (proliferative RET). As with other DM-related comorbidities, excellent blood glucose and blood pressure control can delay the onset or slow the progression of RET. The DCPNS Registry contains a data field for physician diagnosis of RET at time of referral as well as patients self-reported date of routine eye examination for RET. Interestingly, the NDSS does not track RET. There is a paucity of literature detailing how data from patient charts and/or administrative health records can be used to identify cases of RET. The available literature tends to focus on indicators of care like receiving appropriate RET screening. Table 6 displays the data source and RET measures for this literature. Table 6: Literature documenting the measurement of retinopathy Citation Location Data Source Indicator Measurement Patient Chart Data DCPNS Registry Halifax, Nova Scotia Patient chart Physician Dx Administrative Data NDSS Canada Physician v209 [22] Billings Claims & CIHI-DAD Bearelly et United States Practice-based al., 2008 [37] billings database Newton et United States Administrative al., 1999 [38] health records Not measured Evaluated multiple measures: Background RET: ICD-9-CM code of 362.01 but not 362.53 Proliferative RET: ICD-9-CM code of 362.02 but not 362.53 DM Macular edema: ICD-9-CM code of 250.xx with 362.53 Background RET: ICD-9-CM code of 362.01 Proliferative RET: ICD-9-CM code of 362.02 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 17
Chronic Renal Disease Chronic renal disease is a condition marked by a gradual loss of the ability by the kidneys to remove wastes, concentrate urine, and maintain stable fluid, salt, acid, and hormone levels. This chronic condition is one of the most serious and costly complications of DM. The onset and progression of renal disease can be slowed or even prevented through excellent blood glucose and BP control. The DCPNS Registry contains several data fields that can be used independently or in combination to identify CRD cases: physician diagnosis of nephropathy at time of referral, creatinine used to calculate the egfr using both the Modification of Diet in Renal Disease and Cockcroft-Gault formulas, and albumin to creatinine ratio. The NDSS [22] measures chronic or unspecified renal failure and end-stage renal disease; however, these measures are based solely on CIHI-DAD records. There is sparse literature detailing how data from patient charts and/or administrative health records can be used to identify cases of CRF; most available literature deals with the broader category of renal disease. Table 7 displays the data source and measures for CRD (and CRF if available) for a sampling of this literature. Table 7: Literature documenting the measurement of chronic renal disease Citation Location Data Source Indicator Measurement Patient Chart Data DCPNS Registry Halifax, Nova Scotia Patient chart Physician Dx, creatinine (egfr <60ml/min), ACR >2.0 mg/mmol for men or>2.8 mg/mmol for women Borzecki et United States Electronic al., 2004 [34] clinicians notes Renal disease: 1 specific mention of condition * identified by ICD-9-CM code of 403, 405.01, 405.11, 405.91, 582, 583, 585, 586, 593.9 Haroun et al., 2003 [39] Maryland, United States Medical Records Renal disease: ICD-9 code of 250.4, 274.1, 275.4, 403, 404, 580-589, 593.9 Administrative Data NDSS v209 [22] Canada CIHI-DAD Renal disease: 1 hospitalization with an ICD-9-CM code of 585-586 or an ICD-10-CA code of N18-N19 End stage renal disease: 1 hospitalization with an ICD-9-CM code of 585-586; an ICD procedure code of 3995, 5498, 556; a CCP code of 5195, 6698, 6759; an ICD-10-CA code of N18-N19; and/or a CCI code of 1PZ21, 1PC85 Kern et al., United States VA and 2006 [40] Medicare records ICD-9-CM codes of 403.11, 403.91, 404.12, 404.13, 404.92, 404.93, 585-587 18 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Citation Location Data Source Indicator Measurement Li et al., Australia Australia 2004 [41] Bureau of Statistics Data Oliver et al., Ontario, Canada Physician 2003 [42] billings claims Brameld et Australia Hospital al., 1999 [43] morbidity and death records Diabetic renal failure: ICD-10 code of E10.23, E11.23, E13.23, & E14.23 Hypertensive renal failure: ICD-10 code of I12.0, I13.1, I13.2 CRF: ICD-10 code of N18 Unspecified renal failure: ICD-10 code of N19 Chronic dialysis: Cases with physician claims for haemodialysis or peritoneal dialysis delivered at home, in hospital, or at self-care or satellite unit that meet the following criteria Total treatment (Tx) duration (last Tx first Tx) was 90 days after any gaps 21 days between 2 consecutive Tx were subtracted First Tx could be for chronic or acute dialysis Chronic or unspecified renal failure: ICD-9-CM codes of 585, 586 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 19
Survival Analysis Study Population DCPNS Registry Alone (Cohort 1.1) The DCPNS Registry contained 72,317 cases of DM and PreDM as of March 31, 2009. Only cases with type 1 DM only (N=3,467) or type 2 DM only (N=51,895) were included in the Cohort 1.1. All cases with fewer than two DC visits were excluded (N=24,986). Of the 30,376 remaining cases, 2,466 were excluded as they did not have date of diagnosis recorded in the DCPNS Registry. A further 1,494 cases were excluded due to inconsistencies with various date variables (date of diagnosis, date of first DC visit, and date of death), leaving a final intact population of 26,416 (type 1: N=1,825; type 2: N=24,591). Cohort characteristics are presented in Table 8. DCPNS Registry Supplemented with Administrative Health Records (Cohort 1.2) A total of 58,422 prevalent cases from the DCPNS Registry were contributed to the NSDR up to March 31, 2006. Only type 1 (N=3,001) and type 2 DM (N=42,308) cases were included in Cohort 1.2. Of the 45,309 cases, 5,041 were excluded as they did not have date of diagnosis recorded in the DCPNS Registry. A further 1,903 cases were excluded due to inconsistencies with various date variables (date of diagnosis, date of first DC visit, and date of death), leaving a final intact population of 38,365 (type 1: N=2,363; type 2: N=36,002). Cohort characteristics are presented in Table 8. Table 8: Population characteristic by cohort Cohort 1.1 Cohort 1.2 Male Female Missing HTN RET CRD Mean (median) age at DM Dx (in years) Type 1 e Type 2 Mean (median) age at first DC visit (in years) Type 1 Type 2 13,891 (52.6%) 12,500 (47.3%) 25 ( 0.1%) 20,219 (76.5%) 898 ( 3.4%) 7,601 (28.8%) 16.8 (12.9) 55.0 (55.0) 26.5 (22.6) 58.6 (58.7) 20,340 (53.0%) 17,923 (46.7%) 102 ( 0.3%) 30,256 (78.9%) 9,268 (24.2%) 6,660 (17.4%) 20.7 (16.0) 55.9 (55.7) 32.0 (31.1) 59.0 (59.0) Number of deaths 2,455 4,501 e The mean and median age at DM Dx for type 1 cases is higher than expected based on what is known about this population from previous DCPNS work. This variable will be explored in greater detail to determine why the values are higher than expected. 20 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Survival Time DCPNS Registry Alone (Cohort 1.1) The median survival time for deceased patients in Cohort 1.1 was approximately 11.2 person-years. For censored cases, the median follow-up time was 8.0 person-years (see Table 9). DCPNS Registry Supplemented with Administrative Health Records (Cohort 1.2) The median survival time for deceased patients in Cohort 1.2 was approximately 7.2 person-years. For censored cases, the median follow-up time was 6.8 person-years (see Table 9). Table 9: Distribution of survival time (person years) for deceased and censored cases in the DCPNS Registry and DCPNS Registry/Admin cohorts Percentiles Vital Status Sex N Mean Median 25 th 75 th Min Max Cohort 1.1 Deceased M 1,421 12.95 11.00 6.00 18.10 0.03 58.54 F 1,030 13.32 11.40 5.82 19.03 0.09 55.94 All f 2,455 13.11 11.19 5.91 18.51 0.03 58.54 Censored M 12,470 9.58 7.66 3.65 13.25 0.02 69.25 F 11,470 10.41 8.24 3.99 14.25 0.01 65.25 All g 23,961 9.98 8.00 3.83 13.58 0.01 69.25 Cohort 1.2 Deceased M 2,611 9.53 6.82 3.27 13.21 0.01 78.00 F 1,890 10.93 7.92 3.88 16.11 0.04 69.26 All 4,501 10.11 7.23 3.51 14.54 0.01 78.00 Censored M 17,729 8.44 6.75 3.41 11.08 0.01 66.25 F 16,033 9.05 7.00 3.50 11.63 0.02 62.25 All h 33,864 8.73 6.83 3.50 11.24 0.01 66.25 f g h N = 4 deceased cases in Cohort 1.1 were missing information about sex in the DCPNS Registry N = 21 censored cases in Cohort 1.1 were missing information about sex in the DCPNS Registry N = 102 censored cases in Cohort 1.2 were missing information about sex in the DCPNS Registry Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 21
Cases Ascertainment for Comorbid Conditions Hypertension Overall, there was a fair level of agreement for HTN case ascertainment with 69.8% of cases being concordant; the Cohen s kappa was 0.36 with a 95% confidence interval (CI) of 0.35 to 0.37. In total, 5,420 (27,177 21,757) fewer cases of HTN were derived when using the DCPNS Registry compared to the administrative health records. The percent difference in overall cases ascertainment was 14.1%; a considerably lower percentage than the 30.2% of cases that were discordant (see Table 10). Table 10: Case ascertainment for HTN cases derived from the DCPNS Registry versus administrative health records DCPNS Registry Yes No Total Administrative health records Yes 18,678 8,499 27,177 No 3,079 8,109 11,188 Total 21,757 16,608 38,365 % agreement = (18,678 + 8,109)/ 38,365 = 69.8% % discordant = (3,079 + 8,499) / 38,365 = 30.2% Overall case ascertainment: DCPNS: 21,757/38,365 = 56.7% ADMIN: 27,177/38,365 = 70.8% Retinopathy Overall, there was slight agreement for RET case ascertainment with 78.0% of cases being concordant; the Cohen s kappa was 0.11 (95% CI: 0.11 0.12). In total, 7,772 (8,929 1,157) fewer cases of RET were derived when using the DCPNS Registry alone compared to the administrative health records. The percent difference in overall cases ascertainment was 20.3%. Approximately 22.0% of cases that were discordant (see Table 11). Table 11: Case ascertainment for RET cases derived from the DCPNS Registry versus administrative health records DCPNS Registry Yes No Total Administrative health records Yes 818 8,111 8,929 No 339 29,097 29,436 Total 1,157 37,208 38,365 % agreement = (818 + 29,097)/ 38,365 = 78.0% % discordant = (339 + 8,111) / 38,365 = 22.0% Overall case ascertainment: DCPNS: 1,157/38,365 = 3.0% ADMIN: 8,929/38,365 = 23.3% 22 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Chronic Renal Disease Overall, there was slight agreement for RET case ascertainment with 85.2% of cases being concordant; the Cohen s kappa was 0.17 (95% CI: 0.17 0.19). In total, 594 (4,127 3,533) more cases of CRD were derived when using the DCPNS Registry compared to the administrative health records. The difference in overall case ascertainment was 1.6%; however, 14.8% of cases were discordant (see Table 12). Table 12: Case ascertainment for CRD cases derived from the DCPNS Registry versus the administrative health records DCPNS Registry Yes No Total Administrative health records Yes 1,000 2,533 3,533 No 3,127 31,705 34,832 Total 4,127 34,238 38,365 % agreement = (1,000 + 31,705)/ 38,365 = 85.2% % discordant = (3,127 + 2,533) / 38,365 = 14.8% Overall case ascertainment: DCPNS: 4,127/38,365 = 10.8% ADMIN: 3,533/38,365 = 9.2% Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 23
Cumulative Survival Cumulative Survival Cumulative Survival Cum Survival Cumulative Survival Cum Survival Cox Proportional Hazard Models Overall Model For DM, case detection was based solely on the DCPNS Registry. The survival curves for the two cohorts were similar. Cumulative survival began to decline markedly at approximately 25 years post- Dx for type 1 DM cases and at approximately 7-8 years post-dx for type 2 DM cases (see Figure 2). Figure 2: Cox proportional hazard model survival curves by DM type for Cohort 1.1 and 1.2 a) DCPNS Registry Alone (Cohort 1.1) 1.0 1.0 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0.0 0.0 0.00 10.00 20.00 30.00 40.00 Survival Time Years 50.00 60.00 Type 1 Survival Time (person-years) 0.00 10.00 20.00 30.00 40.00 50.00 60.00 Survival Time Years Type 2 Survival Time (person-years) b) DCPNS Registry supplemented by administrative health records (Cohort 1.2) Type 1 Survival Time (person-years) Type 2 Survival Time (person-years) 24 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Cumulative Survival Cumulative Survival Cumulative Survival Cum Survival Cumulative Survival Cum Survival By Sex Sex, as recorded in the DCPNS Registry, was added to the Cox proportional hazard models. Regardless of DM type, females had a longer survival time than males (see Figure 3). The survival curves for males and females began to diverge at approximately 25 years post-dm Dx for type 1 cases and at approximately 5 years post-dm Dx for type 2 cases. Figure 3: Cox proportional hazard model survival curves by DM type and sex for Cohort 1.1 and 1.2 a) DCPNS Registry Alone (Cohort 1.1) Survival Function: Female Male 1.0 1.0 0.8 sex M F 0.8 sex2 M F 0.6 0.6 0.4 0.4 0.2 0.2 0.0 0.0 0.00 10.00 20.00 30.00 40.00 Survival Time Years 50.00 60.00 Type 1 Survival Time (person-years) 0.00 10.00 20.00 30.00 40.00 50.00 Survival Time Years Type 2 Survival Time (person-years) 60.00 b) DCPNS Registry supplemented by administrative health records (Cohort 1.2) Survival Function: Female Male Type 1 Survival Time (person-years) Type 2 Survival Time (person-years) Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 25
Cumulative Survival Cumulative Survival Cumulative Survival Cum Survival Cumulative Survival Cum Survival By Hypertension Hypertension status was added to the Cox proportional hazard models. Regardless of DM type or cohort, those with HTN had a longer survival time than those with no HTN recorded (see Figure 4). The survival curves for those with HTN and those with no HTN recorded began to diverge at approximately 25 years post-dm Dx for type 1 cases and at approximately 5 years post-dm Dx for type 2 cases, with the degree of divergence remaining relatively constant over time. The results were essentially unchanged when sex was added to the models (see Table 13). Figure 4: Cox proportional hazard model survival curves by DM type and HTN status for Cohort 1.1 and 1.2 a) DCPNS Registry Alone (Cohort 1.1) Survival Function: HTN No HTN recorded 1.0 1.0 0.8 HTN_Flag No HTN HTN 0.8 HTN_Flag No HTN HTN 0.6 0.6 0.4 0.4 0.2 0.2 0.0 0.0 0.00 10.00 20.00 30.00 40.00 50.00 60.00 Survival Time Years Type 1 Survival Time (person-years) 0.00 10.00 20.00 30.00 40.00 50.00 Survival Time Years Type 2 Survival Time (person-years) 60.00 b) DCPNS Registry supplemented by administrative health records (Cohort 1.2) Survival Function: HTN No HTN recorded Type 1 Survival Time (person-years) Type 2 Survival Time (person-years) Table 13: Unadjusted and sex-adjusted hazard rate ratios (HRR) for HTN Status by DM type for Cohort 1.1 and 1.2 Cohort 1.1 Cohort 1.2 Type 1 Type 2 Type 1 Type 2 Unadjusted Sex-adjusted 1.51 1.45 1.58 1.55 1.46 1.38 2.19 2.08 26 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Cumulative Survival Cumulative Survival Cumulative Survival Cum Survival Cumulative Survival Cum Survival By Retinopathy Retinopathy status was added to the Cox proportional hazard models. For Cohort 1.1, those with RET had a shorter survival time than those with no RET recorded, regardless of DM type (see Figure 5a). The survival curves for those with RET and those with no RET recorded began to diverge at approximately 25 years post-dm Dx for type 1 cases and at approximately 5 years post-dm Dx for type 2 cases, with the degree of divergence remaining relatively constant over time. For Cohort 1.2, the reverse is true. Those with RET had a slightly longer survival time than those with no RET recorded, regardless of DM type (see Figure 5b). The survival curves for those with RET and those with no RET recorded began to diverge, albeit slightly, at approximately 25 years post-dm Dx for type 1 cases and at approximately 5 years post-dm Dx for type 2 cases, with the degree of divergence remaining relatively constant over time. The results were essentially unchanged when sex was added to the models (see Table 14). Figure 5: Cox proportional hazard model survival curves by DM type and RET status for Cohort 1.1 and 1.2 a) DCPNS Registry Alone (Cohort 1.1) Survival Function: RET No RET recorded 1.0 1.0 0.8 Retin_Flag No Retin Retin 0.8 Retin_Flag No Retin Retin 0.6 0.6 0.4 0.4 0.2 0.2 0.0 0.0 0.00 10.00 20.00 30.00 40.00 Survival Time Years 50.00 60.00 Type 1 Survival Time (person-years) 0.00 10.00 20.00 30.00 40.00 50.00 Survival Time Years Type 2 Survival Time (person-years) 60.00 b) DCPNS Registry supplemented by administrative health records (Cohort 1.2) Survival Function: RET No RET recorded Type 1 Survival Time (person-years) Type 2 Survival Time (person-years) Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 27
Table 14: Unadjusted and sex-adjusted hazard rate ratios (HRR) for RET Status by DM type for Cohort 1.1 and 1.2 Cohort 1.1 Cohort 1.2 Type 1 Type 2 Type 1 Type 2 Unadjusted Sex-adjusted 0.49 0.55 0.78 0.78 1.22 1.26 1.23 1.23 By Chronic Renal Failure Chronic renal disease status was added to the Cox proportional hazard models. For Cohort 1.1, those with CRD had a slightly longer survival time than those with no CRD recorded, regardless of DM type (see Figure 6a). The survival curves for those with CRD and those with no CRD recorded began to diverge at approximately 25 years post-dm Dx for type 1 cases and at approximately 10 years post- DM Dx for type 2 cases, with the degree of divergence remaining relatively constant over time. For Cohort 1.2, type 1 DM cases with CRD had a shorter survival time than those with no CRD recorded (see Figure 6b), with the survival curves beginning to diverge at approximately 20 years post- DM Dx. For type 2 DM cases, the survival curves for those with CRD and those with no CRD recorded were virtually coincident. The results were essentially unchanged when sex was added to the models (see Table 15). 28 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Cumulative Survival Cumulative Survival Cumulative Survival Cum Survival Cumulative Survival Cum Survival Figure 6: Cox proportional hazard model survival curves by DM type and CRD status for Cohort 1.1 and 1.2 a) DCPNS Registry Alone (Cohort 1.1) Survival Function: CRD No CRD recorded 1.0 1.0 0.8 Renal_Flag No Renal Disease Has Renal DIsease 0.8 Renal_Flag No Renal Disease Has Renal DIsease 0.6 0.6 0.4 0.4 0.2 0.2 0.0 0.0 0.00 10.00 20.00 30.00 40.00 Survival Time Years 50.00 60.00 Type 1 Survival Time (person-years) 0.00 10.00 20.00 30.00 40.00 50.00 Survival Time Years Type 2 Survival Time (person-years) 60.00 b) DCPNS Registry supplemented by administrative health records (Cohort 1.2) Survival Function: CRD No CRD recorded Type 1 Survival Time (person-years) Type 2 Survival Time (person-years) Table 15: Unadjusted and sex-adjusted hazard rate ratios (HRR) for CRD Status by DM type for Cohort 1.1 and 1.2 Cohort 1.1 Cohort 1.2 Type 1 Type 2 Type 1 Type 2 Unadjusted Sex-adjusted 1.43 1.38 1.28 1.20 0.55 0.56 0.98 1.03 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 29
Sensitivity Analysis Study Population A total of 58,422 prevalent cases from the DCPNS Registry were contributed to the NSDR up to March 31, 2006; 48,432 of these cases had a matching record in the NDSS. Of the 48,432 cases common to both datasets, 6,899 i were excluded as they did not have date of diagnosis recorded in the DCPNS Registry. Of the 41,533 remaining cases, 37,798 had a clinically confirmed diagnosis of type 1 (N=2,742) or type 2 (N=35,056) DM in the DCPNS Registry. It is noteworthy that of the 3,993 cases in the DCPNS Registry who presented with PreDM only, approximately one third (N=1,344) appeared in the NDSS as type1/type2 DM. A total of 1,934 of the common cases were excluded due to inconsistencies with various date variables (date of diagnosis, date of first DC visit, and date of death) leaving 35,864 type 1 and type 2 cases in the cohort. The sample was further restricted to fiscal years 1998/99 2005/06 to account for the mix of prevalence and incident cases in the early years of the NDSS (see Table 16). The 21,397 cases identified in the NDSS from 1998/99 forward were assumed to be incident cases. Among this population, there were 860 type 1 cases, of whom 15 died by March 31, 2006. The number of deaths among type 1 cases was too low to provide meaningful results so they were excluded, leaving a final intact sample of 20,537 type 2 cases identified in the NDSS from 1998/99 to 2005/06. Table 16: Number of type 1 and type 2 DM cases by fiscal year of identification in the NDSS Fiscal Year DM Type j Type 1 Type 2 Total 1996/97 1,422 10,009 11,431 1997/98 171 2,865 3,036 1998/99 129 2,694 2,823 1999/00 117 2,716 2,833 2000/01 120 2,642 2,762 2001/02 105 2,628 2,733 2002/03 94 2,574 2,668 2003/04 92 2,494 2,586 2004/05 96 2,595 2,691 2005/06 107 2,194 2,301 Total 2,453 33,411 35,864 i j The high number of records missing date of Dx was due to an error that occurred when DCPNS merged its data. This error was corrected; however, time constraints precluded re-running the data in time for this report. As recorded in the DCPNS Registry 30 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Just over half of the study population was male (Male: N=10,986; Female: N=9,500; Unknown: N=51). Mean age at DM diagnosis, age group at DM diagnosis, number of HTN cases, and number of deaths are presented separately for the DCPNS Registry and the NDSS (see Table 17). Table 17: Population characteristic by data source Population Characteristic DCPNS NDSS Mean age at DM Dx 56.2 years 57.6 years Median age at DM Dx 55.9 years 57.3 years Frequency by age group 0 39 years 40 49 year 50 59 years 60 69 years 70 years unknown 2,133 4,335 6,235 4,568 3,215 51 1,732 3,919 6,201 4,891 3,793 51 Number of HTN cases identified 11,818 13,317 Number of deaths 1,319 1,326 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 31
Comparison of DCPNS Registry and NDSS Data Date of Diagnosis On average, DM diagnoses recorded in the DCPNS Registry occurred 1.5 years earlier than those recorded in the NDSS. This distribution was right skewed, with the median difference in date of DM diagnosis being 0.2 years earlier in the DCPNS Registry. Over time, the distribution of differences narrowed (see Table 18). Table 18: Distribution of differences (years) between the dates of diagnosis recorded in the DCPNS Registry versus the NDSS by fiscal year of identification in the NDSS Fiscal Year N Mean Median Percentiles 25 th 75 th Min Max Overall 20,537 1.47 0.22 0.07 1.14-7.58 52.64 1998/99 2,694 2.11 0.27 0.07 2.01-7.58 40.87 1999/00 2,716 1.69 0.26 0.07 1.36-6.42 38.47 2000/01 2,642 1.56 0.22 0.07 1.26-5.63 42.39 2001/02 2,628 1.26 0.22 0.07 1.09-4.41 42.21 2002/03 2,574 1.31 0.20 0.07 1.00-3.40 52.64 2003/04 2,494 1.27 0.21 0.07 1.06-2.53 45.58 2004/05 2,595 1.19 0.20 0.07 0.87-1.61 30.20 2005/06 2,194 1.25 0.21 0.07 0.93-0.78 33.64 32 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Survival Time The median survival time for deceased patients in the DCPNS Registry was approximately one year longer than that for deceased patients in the NDSS (see Table 19). For censored cases, the median follow-up time derived from the DCPNS Registry was less than a year longer than that derived from the NDSS. Table 19: Distribution of survival time (person years) for deceased and censored cases in the DCPNS Registry and NDSS (1998/99 2005/05) Percentiles Vital Status Sex N Mean Median 25 th 75 th Min Max DCPNS Registry Deceased M 781 5.14 3.80 1.91 6.05 0.06 49.26 F 538 5.37 4.02 2.14 6.43 0.09 47.20 All 1,319 5.23 3.89 2.00 6.19 0.06 49.26 Censored M 10,205 5.31 4.75 2.50 6.92 0.02 56.24 F 8,962 5.54 4.83 2.58 7.08 0.05 48.24 All k 19,218 5.42 4.79 2.55 7.00 0.02 56.24 NDSS Deceased l M 781 2.95 2.71 1.24 4.43 0.00 7.99 F 538 2.92 2.71 1.11 4.50 0.00 7.63 All m 1,326 2.94 2.71 1.20 4.44 0.00 7.99 Censored M 10,205 4.02 4.04 2.02 6.00 0.00 8.00 F 8,962 4.01 3.99 2.02 5.97 0.00 8.00 All n 19,211 4.01 4.01 2.02 5.98 0.00 8.00 k l m n N=51 cases were missing information about sex in the DCPNS Registry There were 7 more deaths recorded in the NDSS than in the DCPNS Registry N=7 of the deceased cases were missing information about sex in the DCPNS Registry N=44 of the censored cases were missing information about sex in the DCPNS Registry Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 33
Case Ascertainment for Hypertension o Overall, there was moderate agreement for HTN case ascertainment with 73.3% of cases being concordant; the Cohen s kappa was 0.44 (95% CI: 0.43 0.45). In total, 1,499 (13,317 11,818) fewer cases of HTN were derived from the DCPNS Registry compared to the NDSS (see Table 20). Although there was relatively little difference in overall case ascertainment (7.3%), the case assignment differed markedly between the two sources, with over 25% of cases being discordant (see Table 20). Table 20: Case ascertainment for HTN cases derived from the DCPNS Registry versus the NDSS DCPNS Registry Yes No Total NDSS Yes 9,821 3,496 13,317 No 1,997 5,223 7,220 Total 11,818 8,719 20,537 % agreement = (9,821 + 5,223) / 20,537 = 73.3% % discordant = (1,997 + 3,496) / 20,537 = 26.7% Overall case ascertainment: DCPNS: 11,818 / 20,537 = 57.5% ADMIN: 13,317 / 20,537 = 64.8% Kaplan Meier Survival Curves Overall, the median survival time from date of DM diagnosis to date of death or end of the study period derived from the DCPNS Registry was 43.17 years (see Figure 7a); with males having a slightly shorter median survival time than females: 39.8 person-years for males versus 44.4 person-years for females (see Figure 7b). The median survival time was also slightly shorter for individuals with a record of HTN in the DCPNS Registry (39.8 person-years) compared to those with no record of HTN (44.0 person-years); however, for the first 35 years, this situation is reversed (see Figure 7c). Median survival times could not be estimated using the NDSS. Kaplan Meier survival curves based on NDSS data showed a slightly longer survival time for females over males (see Figure 7b) and for individuals with no record of HTN over those with a record of HTN (see Figure 7c). o Analyses were not performed for RET and CRD as the prevalence of these comorbidities was low in Cohort 1.1 of the survival analyses the prevalence would be even lower for the DCPNS/NDSS common cohort 34 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Cumulative Survival Cumulative Survival Cumulative Survival Cumulative Survival Cumulative Survival Cumulative Survival Figure 7: Kaplan Meier survival curves derived from the DCPNS Registry versus NDSS a) Overall Survival Survival Function Censored DCPNS Survival Time (person-years) NDSS Survival Time (person-years) b) Survival by sex Survival Function: Male Female Censored: Male Female DCPNS Survival Time (person-years) NDSS Survival Time (person-years) c) Survival by HTN status Survival Function: HTN HTN not recorded Censored: HTN HTN not recorded DCPNS Survival Time (person-years) NDSS Survival Time (person-years) Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 35
Cumulative Survival Cumulative Survival Cox Proportional Hazard Models The relationship between HTN status and survival was examined using Cox proportional hazard models to control for age at DM diagnosis, sex, and a sex by HTN status interaction. The resulting survival curve derived from DCPNS Registry data showed a longer survival time for those with a record of HTN in the DCPNS Registry over those without a record of HTN, and this advantage was consistent across the entire time span (see Figure 8). The same analysis was conducted using the NDSS data. The resulting survival curve reversed direction from the Kaplan Meier curve (see Figure 7c), now showing a longer survival time for those with a record of HTN over those without a record of HTN (see Figure 8). Figure 8: Cox proportional hazard model survival curves by HTN status derived from the DCPNS Registry versus NDSS (adjusted for age at DM diagnosis, sex, and a sex by HTN status interaction) Survival Function: HTN HTN not recorded DCPNS Survival Time (person-years) NDSS Survival Time (person-years) 1.0 0.9 0.0 2.0 4.0 6.0 8.0 Test of the Provisional Nova Scotia Diabetes Repository After an outstanding issue with the PIA amendment for the provisional NSDR was clarified (Feb 2009 Nov 2009), the process to access data from the DCPNS Registry, CIHI-DAD, MSI Claims, MSI Registry, and the NDSS took 6 weeks in total. It took approximately one week to prepare the Application for Access to Provisional NSDR. The NSDR partners received the submission on October 28, 2009 and approval with no revisions was granted by all partners by November 9, 2009; this work was done in advance of receiving written approval for the NSDR PIA amendment. A data extraction request (part of the Application for Access to Provisional NSDR) was sent to the team lead for the provisional NSDR Technical Support Team, and the data extraction process was triggered by November 12, 2009. Data from the DCPNS Registry were extracted and placed in a project based folder at the NS DoH within one day of receiving the data extraction request. Three separate files were extracted by the NS DoH Information Management Services and placed in the project based folder by 36 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
December 9, 2009. There was a slight delay in receiving security clearance for the project manager and project analyst; however, this issue was resolved within a week and user accounts were created by December 7, 2009. Analytic work using the linked administrative health records and the NDSS began in December 2009 and concluded March 2010. Stakeholder Consultation Division of Endocrinology, Dalhousie University On February 16, 2010, five endocrinologists from the Division of Endocrinology at Dalhousie University participated in the 90-minute focus group. DM Severity The endocrinologists unanimously stated that DM severity was not a useful concept. They noted that DM is a chronic multi-factorial disease that can be labelled as severe along numerous dimensions including complications, quality of life, and psychological wellbeing to name a few. It was also noted that DM severity was a subjective term a provider s perception of a severe case is often quite different from a patient s perception. The notion of risk of complications arose frequently during the discussion about DM severity, with a particular emphasis on the risk of cardiovascular complications. It was noted that all DM patients are somewhere along the progression from no complications to one or more complications. A number of factors associated with an increased risk for complications were discussed (see Table 21): Table 21: Factors associated with risk of complications for DM patients Risk Factor Low risk for complications High risk for complications Type of DM Type 1 GDM + high A1C DM Duration < 5 years > 10 years Age DM Treatment Compliance with clinical practice guidelines Patient behaviour / circumstances 45 years (men) 50 years (women) diet / exercise, and/or oral agent(s), and/or single insulin All outcomes at or close to target Patient has social supports Patient actively self-manages DM > 45 years (men) > 50 years (women) 2 types of insulin No outcomes at target Patient lives alone Pt does not self-manage DM Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 37
Data Requirements for DM Portrayal The endocrinologist had a number of suggestions regarding how DM-related data could be presented to provide a more complete picture of the nature and course of DM in the province. A key message was that data should be presented as concisely as possible and any practice recommendations stemming from the data should be highlighted. It was noted that group-level data should be presented to help show the burden of DM in the province, stratifying by outcome (i.e., DM is well managed, DM not well managed) and highlighting patient and DC characteristics for these groups. Interest was also expressed in sub-group analyses; for example, the best and worst outcomes among insulin users. Other variables of interest for sub-group analyses included 5-year age group, DM duration, DM treatment type, presence of complications, and type of healthcare provider. Outcomes improved by glycaemic control were also of interest (e.g., A1C, weight loss, blood pressure, etc.) as were 5-year time trends. Diabetes Centre Educators Between February 16 and March 3, 2010, 16 DM educators, from 19 of 39 DCs in 7 of 9 DHAs and the IWK Health Sciences Centre, participated in 1 of 4 focus groups (N=3 to 5 per session). Additional feedback related to outstanding questions during the phone conversations was contributed by e-mail. The educators represented 10 full-time DC operations (including a specialty paediatric and an adult only program) and 6 part-time/less than part-time operations (i.e., 1-3 days/week). The case mix for full-time DCs often encompasses all ages and all types of DM adults, paediatrics, and pregnant women while the case mix for part-time/less than part-time DCs is predominantly adults with type 2 diabetes. This operation mix is important to note, as the populations accessing the smaller part-time/less than part time programs will be more rural and less diverse by age and DM type than those accessing the full-time programs. Following a lead in and icebreaker exercise, educators were asked to estimate what proportion of their patient population would be of low severity and high severity. Educators reported that between 5 and 40% of their patient populations were high severity; close to 90% (14 of 16) of responses were between 20 and 33%. For part-time programs, 10 to 25% of their populations were estimated to be high severity; close to 70% (4 of 6) of responses were between 20 and 25%. Educators reported that between 25 and 80% of their patient populations were low severity; close to 80% (13 of 16) of all responses were between 33 and 50%. For part-time programs, all responses (6 of 6) were between 33 and 50%. 38 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
DM Severity Diabetes severity was a difficult concept for some of the DM educators. Considerable time was spent trying to articulate a word or expression that would best capture the intent of the descriptor. The educators suggested that time spent counselling as well as informing and engaging others in support of improved management should be considered when trying to differentiate between cases based on DM severity or intensity of care. Additional terms offered for consideration include the following: Situation of most concern Level of care (1, 2, 3) Gravity Difficult management Complexity of care/management Inability of the person to self-manage If using level of care, it was suggested that individuals may be able to move between levels depending on the degree of dependency and support required. There was little clear direction with regards to severity being used as a term to indicate long-term risk for morbidity or mortality. When trying to define cases by level of DM severity, the following concepts emerged (see Table 22): Table 22#: Concepts associated with DM severity Concept Severity Patient Characteristics Metabolic Control Self- Management Presence of Complications and/or Comorbidities High Low High Low High Low Individuals with frequent hypoglycaemia and/or bouts of hyperglycaemia (hypoglycaemia unawareness) who are considered to be poorly controlled/unstable (i.e., high A1Cs, symptomatic, and/or with ketoacidosis). Individuals with well-controlled DM (i.e., low A1C at/or close to target) in the presence of no or small amounts of medication and with other blood work and key measures (e.g., foot risk, BP, etc.) within/close to established targets Individuals who have difficulty with self-management Individuals who are educated, informed, motivated, keen to selfmanage, and can demonstrate self-management behaviours (cited for adults only) Individuals with established cardiovascular disease as well as microvascular diseases (e.g., CRD) that make treatment and overall management more challenging for both the individual and the team members. These advanced disease processes impact care, treatment regimens, and medication choices. Other health problems that complicate care include dementia, cancer, cystic fibrosis, and longstanding obesity. Individuals with few or no comorbidities/chronic conditions (i.e., uncomplicated) Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 39
Concept Severity Patient Characteristics Age High Elderly individuals on medications were identified as a vulnerable group as they can move rapidly from stable, uncomplicated, selfreliant care to severe in their care requirements (e.g., rapid deterioration, decompensation, functional dependency, impaired decision-making, etc.) Low - DM Type High Individuals with type 1 DM including children, adults, and pregnant women who require considerable resources and frequent adjustments to treatment plans Mental Health and Social Supports Low High Low Individuals with PreDM or newly diagnosed type 2 DM who are managed with diet only or oral agents and have no comorbidities Individuals with physical, financial, and/or emotional issues that impact self-care and the ability to access necessary supports (e.g., required follow-up, necessary medications) as well as those who struggle with depression that impacts their capacity to manage their diabetes Individual who have supports and access to community resources, are not socially stressed, and have no social concerns Educators were asked to provide a list of the top indicators for determining DM severity or intensity of care. The following are the top three to five indicators listed in order of importance. A1C, BP, and lipid values (A1C was by far the most common choice of these measures) Comorbidities (multiple, not well controlled) Duration of disease Age (young children and elderly) Type of DM (type 1 for all ages) Complex care (difficult to manage, complicated DM) Acute complications (hypoglycaemia, hyperglycaemia, and ketoacidosis) Dementia/mental health (cognition) Poor social and family supports (including financial constraints) Data Requirements for DM Portrayal Diabetes educators reported that they use DM data to look for trends from month-to-month and yearto-year, to make comparison across programs, to make planning decisions (e.g., more or new group programs, more time for insulin starts, more space, etc.), to share with others (e.g., family physicians, management, community partners, etc.), and to support proposal for grant funding. The DM educators recommended that a summary page of DM data would be useful when reporting to senior management (e.g., VPs) and that the summary should include a description of the DC population (i.e., what makes it different/unique). The educators also suggested that data about the total number of individuals and visits (on average) by treatment type and by visit type would be helpful. This format of reporting would also apply to the phone calls made to the DC (i.e., how many 40 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
individuals made calls and the average number of calls per individual overall and by DM and treatment type). DCPNS provides an Indicator Report to all DCs using the on-site DCPNS Registry (31 of 39 provincially p funded DCs currently use the on-site Registry with the remaining DCs anticipated to be using the on-site Registry within the year). Educators receiving and using this report overwhelmingly supported its usefulness. Both the interpretation sheet (with red highlights) and the full report (with detailed tables) were felt to be very useful/helpful. Educators reported that this report allowed their DCs to focus on areas that need improvement in recording key measures. In addition, the comparison from year-to-year has resulted in quality improvement initiatives and added program focus in areas that have impacted patient outcomes. Educators noted that this report provides more than numbers and has been used as the basis of informing management and area physicians about the DC s progress and areas of greatest pride (numbers within target) and/or concern (requiring additional work). There were a number of thoughtful suggestions for improving some data elements already present in the DCPNS Registry as well as collecting additional information. The educators suggestions related to increasing their understanding about individual utilization of and/or need for specific services (e.g., telephone support, referrals, etc.) and to flagging records for patients with values above recommended targets and/or in need of specific tests and examinations. Interest was expressed in reporting the time spent with specific categories of patients to better support/reflect the type of work educators do. Educators supported the idea of reporting data in keeping with the concept of severity (number of comorbidities and time spent per patient). Additional suggestions included the following: A1C presented by duration of DM and determinants of health Number of patients with a combination of indicators/measures in or out of target range (i.e., A1C, BP, lipids) Number of patients using medication and number of medications used Indication of social support and financial situation Copying/self-care capabilities Number of other complications/comorbidities (including ketoacidosis) Hypoglycaemia unawareness Mental health status (e.g., depression, anxiety, etc.) Complexity of treatment Referrals to others (e.g., clinics, specialties, etc.) Outcomes such as stroke, foot procedures, creatinine clearance, etc. GPs, specialist, and emergency room (ER) visits Hospitalizations Looking to the future, one DM educator expressed a desire to capture more variables that would contribute to a specific care plan, similar to a nursing lesson plan. Reporting these variables would provide more information about the patient, including symptoms and complaints (e.g., shortness of breath, sleep apnoea, respiratory problems, A1C, etc.) and would result in a more specific action plan for the person with DM and his/her care provider. p The two federally funded DCs do not use the DCPNS on-site Registry Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 41
Diabetes Centre Managers DC Managers from 3 of the 9 DHAs participated in the 60-minute DC Manager focus group; an additional DC Manager responded to the focus group questions by e-mail. Full and part-time DC operations, providing services to diverse diabetes populations (by age and DM type), were represented. Managers reported that their DHAs were at various stages of developing primary health care teams, reflecting a growing interest in chronic disease management. These teams currently look different by community and DHA, depending on available teams/providers. DM Severity All DC Managers linked DM severity to time, with the most severe cases taking the most time for DC staff to manage/support. Included in this group were insulin starts, pregnancy care, pump patients, and patients with complications (e.g., pre-renal/renal, those requiring internist intervention, etc.). Citing the DCPNS Triage criteria for initial and follow-up visits (see Appendix D), Managers referred to the urgent/semi-urgent categories as an indicator of high severity. Once prompted, case complexity was discussed. The DC Managers noted that severe DM cases are those who would benefit from support beyond that of the current DC team; for these individuals, a case management approach would provide access to other professionals to help address complex needs (psychosocial and financial needs, management of established complications that are progressive in nature, etc.). Other examples of severe DM cases were those who experienced crisis situations (i.e., requiring ER visits) and very high glucose levels. The DC Managers were asked to provide a list of the top indicators for determining DM severity. The following are the top three to five indicators listed in order of importance A1c > 9% Comorbidities Complications (e.g., established heart disease) Psychosocial difficulties Difficulty managing (e.g., non-compliant) Mental health/social supports Self-management capacity Data Requirements for DM Portrayal As with the diabetes educators, DC Managers reported that they use DM data to look for trends over time, to improve efficiencies, and to compare between their programs and across programs of similar size. There was a recognition that the volume of DM data provided by DCPNS may be underutilized and that some parts of the data reports were very busy. Managers highlighted the value of face-to-face presentations to help explain and highlight the most relevant aspects of the DM data. They also valued having a brief written interpretation of the data at the front of data reports as well as having the ability to request custom reports. These custom reports, for example, have been used to understand the impact of activity/exercise programming (e.g., who is attending, and is it making a difference). The DCPNS On-site Indicator Report was cited specifically for the role it plays in quality improvement initiatives that lead to focussed interventions. In one DHA, data from the DCPNS On-site Indicator Report was used to support a shared approach to addressing a 42 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
specific quality care issue about the need to conduct foot assessments despite having no time and limited staff to do so. As result of data presented in the DCPNS On-site Indicator Report, staff came together to generate a solution, pooled educator resources from across the DHA, shared the workload, and completed the necessary assessments on an identified/invited group of patients. Requested improvements to data collection and presentation included revisiting the value of collecting continued insulin start information, the addition of a glossary to explain some of the terms used in the DC Statistics Reports, and additional information related to referrals (who is referring and from where). Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 43
Chapter 4: Discussion Key Learnings Survival Analysis This project was an opportunity to gain insight into the progression of DM including the development of comorbidities within a large population-based cohort of clinically confirmed DM cases. Contrary to expectations, sex appeared to be an independent risk factor in the progression of DM, but it did not act as a confounder in the relationship between HTN and survival. This finding held true across both cohorts, both DM types, and all comorbidities. The analysis revealed that the presence of comorbidity played a role in time to death; although, not always in the expected direction. Results derived from the DCPNS Registry alone (Cohort 1.1) indicated that the presence of HTN and CRD were favourable in terms of survival time, with the nature and size of these differences varying for type 1 and type 2 DM. It was anticipated that this problem would be alleviated when the DCPNS Registry records were supplemented with comorbidity information from administrative health records (i.e., CIHI-DAD and MSI Claims). In reality, this linkage did not resolve the problem and, in fact, generated additional questions that require additional exploration. The broad case definitions used to identify comorbidity cases in the administrative health data were not helpful, as indicated by the low kappa statistics across the three comorbidities. That being said, it is concerning that a substantial proportion of the known comorbidity cases in the DCPNS Registry were not being identified using the administrative health data, even with this most liberal case definition. This finding calls into question the use of these data for estimation of comorbidity burden, especially given that the problem would be compounded for sub-group analyses across multiple comorbidities. Given the short period of time for the analytic work involving the administrative data, it was not possible to explore the date of onset of the comorbidities relative to the date of DM Dx, which may have explained some of the results. It is quite possible that compared to people without HTN, those with pre-existing HTN may be more aggressively screened for DM, resulting in an earlier diagnosis. Additionally, people with DM and HTN may be more aggressively managed than those with DM alone. It is known that the DCPNS Registry likely under-ascertains cases of comorbidity, especially in the early years. The DCPNS Registry was initially developed as a true Registry, capturing information about DC patients at the time of their first visit, but not following them forward through time. Over time, the DCPNS Registry has evolved into a longitudinal database to meet the growing need of DC staffs to use the Registry for monitoring the ongoing management of their patients. This project provided an opportunity to explore the DCPNS Registry from a longitudinal, person-level perspective. Lessons learned have already resulted in some enhancements in data quality and will continue to inform quality improvement initiatives. 44 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Comparison of the DCPNS Registry and NDSS Results from the comparisons of date of DM Dx derived from the DCPNS Registry versus the NDSS showed that the median/mean difference between the two dates was minimal and that it decreased over time. However, the results were markedly different when analysing the survival curves because of how skewed the DCPNS Registry survival times were relative to those of the NDSS. To some extent, the difference in distributions of survival times is an artefact of the data structure in that NDSS lefttruncates the date of Dx for DM cases. It was believed that restricting the cohort to more recently diagnosed cases (i.e., incident NDSS cases from 1998/99 forward) might alleviate this problem; however, the problem persisted. The obvious concern for using survival analysis methodologies with the NDSS is that there is too short of a follow-up period to allow enough events for analysis. As was the case with the administrative health data above, agreement between the NDSS and the DCPNS Registry was not optimal for HTN status. Although the prevalence figures were not that different, the 2x2 table indicated that the two definitions actually identified very different populations. This finding is of particular concern given the number of known HTN cases in the DCPNS Registry that were not identified through the NDSS case definition. It would be interesting to explore these differences separately for type 1 and type 2 DM cases, where type 1 cases by definition have a longer survival given the early age at Dx and might be more susceptive to the impact of left-censoring than the type 2 cases. In keeping with results from the survival analysis, sex did not appear to confound the relationship between HTN and survival for the Cox model derived from DCPNS Registry data. Results derived using the NDSS data did indicate that sex was a confounder; however, more exploratory work is needed to confirm this finding. Based on this preliminary analysis, Kaplan Meier survival curves (i.e., unadjusted) derived from the NDSS data showed that those with HTN die earlier than those with no record of HTN. Survival curves derived from the Cox proportional hazard model that controlled for sex showed the opposite result: those with HTN survive longer than those with no record of HTN. This finding again calls into question the suitability of using survival analysis methodologies with the NDSS data. Test of the Provisional Nova Scotia Diabetes Repository The NSDR process proved to work very smoothly, with the only concern being the delay in receiving the PIA approval. Unfortunately, this delay greatly impacted the work dependant on data linkages with administrative health records and the NDSS, leaving insufficient time to pursue many of the analyses in further detail. However, given that the permissions are currently in place and not timelimited, the door is open to pursuing many of the questions above without additional time delays. Another concern with the NSDR is that the data are only current through 2005/06 at this point in time. For the purpose of comparing the DCPNS Registry with the NDSS, the addition of data from fiscal years 2006/07 2009/10 would greatly increase the sample size and follow-up time for analysis. Stakeholder Consultation The stakeholder consultations proved to be very helpful for understanding how various DM experts interpret the term DM severity, how they would like to use DM data to better understand the burden of DM, and how that data can be presented most effectively. Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 45
Endocrinologists, DC educators, and DC managers alike struggled with the concept of DM severity, many stating that the term was not particularly helpful within the context of a chronic multi-factorial disease like DM. When encouraged to identify indicators that differentiate between less and more severe DM cases, all groups suggested similar lists that included clinical values (e.g., A1C), DM type and duration, complications and comorbidities, and case complexity as well as measures of mental health/wellbeing and social support. The only difference between the groups was that the endocrinologists focussed primarily on factors associated with cardiovascular risk, whereas DC educators and managers focussed on the time required to manage DM cases. The DCPNS has a mandate to collect, analyze, and distribute diabetes-related data for Nova Scotia. As a result of these stakeholder consultations, DCPNS now has an increased awareness of the data requirements for different end-user groups and how best to present the data. The endocrinologists do not routinely receive data from DCPNS; thus, were unfamiliar with some the DCPNS reports. A key message from this group was to present data in a very concise manner, highlighting any practice recommendations stemming from the data. The DC educators and managers were more familiar with DCPNS data and reports; thus, they provided much more detailed feedback regarding data requirements and presentation formats. Both DC educators and managers valued oral presentation of the data, which allow for discussion of the data and its implications. Next Steps Although the final deliverable for this project is complete, the work initiated through this project will continue. First, this report will be shared with the project Advisory Group and other interested stakeholders (e.g., DCPNS Advisory Council, DC educators/managers, Network for End of Life Studies, Division of Endocrinology, etc.). Due to time constrains, the preliminary indicators for comorbidity were not refined (i.e., alternate case definitions were not tested); this work is a top priority for DCPNS in the next few months. Some interesting research ideas relating to this work have already been suggested and the sharing of the report is bound to stimulate even more. The Department of Ophthalmology at Dalhousie University expressed interest in using the DCPNS Registry to explore trajectories relating to eye care among DM patients (e.g., how many DM patients have an annual eye exam, with the appropriate profession how many have background / proliferative RET, at what point were patients referred to optometrists and ophthalmologists, etc.). Members of the Division of Endocrinology at Dalhousie expressed interest in understanding how markers of disease progression are related to survival. The DCPNS also plans to peruse a number of issues related to this project internally; for example, the DCPNS-NDSS comparison will be re-run using more recent years of data (up to 2009/10). Case ascertainment for comorbidities is best in the most recent years of the DCPNS Registry (2002/03 forward). This work will provide a more in depth understanding of the comorbidity data contained in the DCPNS Registry. This knowledge will, in turn, inform initiatives to improve the completeness of Registry data. 46 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
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19. O Hare AM, Glidden DV, Fox CS, Hsu C. High prevalence of peripheral arterial disease in persons with renal insufficiency: results from the national Health and Nutrition Examination Survey 1999-2000. Circulation. 2004;109:320-323. 20. Golden SH, Peart-Vigilance C, Koa WH, Brancati FL. Perioperative glycaemic control and the risk of infectious complications in a cohort of adults with diabetes. Diabetes Care. 1999;22(9):1408-1414. 21. Canadian Institute for Health Information. Data Quality Documentation: Discharge Abstract Database 2001-2002. Ottawa, Canada: Canadian Institute for Health Information 2003. 22. Public Health Agency of Canada, National Diabetes Surveillance System v209 Documentation. 2009. 23. Mubarak FM, Froelicher ES, Jaddou HY, Ajlouni KM. Hypertension among 1000 patients with type 2 diabetes attending a national diabetes center in Jordan. Ann Saudi Med. 2008;28(5):346-351. 24. Petrella RJ, Merikle E. A retrospective analysis of the prevalence and treatment of hypertension and dyslipidema in southwestern Ontario, Canada. Clin Ther. 2008;30(6):1145-1154. 25. Sturkenboom MCJM, Dielman JP, Picelli G, et al. Prevalence and treatment of hypertensive patients with multiple concomitant cardiovascular risk factors in the Netherlands and Italy. J Hum Hypertens. 2008;22:704-713. 26. Turner BJ, Hollenbeak CS, Weiner M, Have TT, Tang SSK. Effect of unrelated comorbid conditions on hypertension management. Ann Intern Med. 2008;148:578-586. 27. Hicks LS, Shaykevich S, Bates DW, Ayanian JZ. Determinants of racial/ethnic differences in blood pressure management among hypertensive patients. BMC Cardiovasc Disord. 2005 Jun 22;5(16). 28. Russell C, Dunbar P, Salisbury S, Sketris I, Kephart G. Hypertension control: results from the Diabetes Care Program of Nova Scotia registry and impact of changing clinical practice guidelines. Cardiovasc Diabetology. 2005 Jul 20;4(11). 29. McDonald K, McCrea P, Reimer, K. Hypertension administrative data case definition comparison. 2008 May 14; Prepared for NDCSS Scientific Working Group and The Task Group on Chronic Disease and Injury Surveillance. 30. Tu K, Chen Z, Lipscombe LL. Prevalence and incidence of hypertension from 1995 to 2005: a populationbased study. CMAJ. 2008;178(11):1429-1440. 31. Wiréhn ABE, Karlsson HM, Carstensen JM. Estimating disease prevalence using a population-based administrative healthcare database. Scand J Public Health. 2007;35:424-431. 32. Bullano MF, Kamat S, Willey VJ, Barlas S, Watson DJ, Brenneman SK. Agreement between administrative claims and the medical record in identifying patients with a diagnosis of hypertension. Med Care. 2006;44(5):486-490. 33. Barron JJ, Al-Zakwani I, Iarocci T. Quality of care and attributable healthcare costs in diabetic hypertensive patients initiated on calcium antagonist therapy. Clin Drug Invest. 2004;24(11):641-649. 34. Borzecki AM, Wong AT, Hickey EC, Ash AS, Berlowitz DR. Identifying hypertension-related comorbidities from administrative data: what s the optimal approach? Am J Med Qual. 2004; 19(5):201-206. 35. Rector TS, Wickstrom SL, Greenlee NT, et al. Specificity and sensitivity of claims-based algorithms for identifying members of Medicare+Choice health plans that have chronic medical conditions. Health Serv Res. 2004;39(6):1839-1857. 36. Lund BC, Perry PJ, Brooks JM, Arndt S. Clozapine use in patients with schizophrenia and the risk of diabetes, hyperlipidemia, and hypertension. Arch Gen Psychiatry. 2001;58:1172-1176. 48 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
37. Bearelly S, Mruthyunjaya P, Tzeng JP, et al. Identification of patients with diabetic macular edema from claims data. Arch Ophthalmol. 2008;126(7):986-989. 38. Newton KM, Wagner EH, Ramsey SD, et al. The use of automated data to identify complications and comorbidities of diabetes: a validation study. J Clin Edidemiol. 1999;52(3):199-207. 39. Haroun MK, Jaar BG, Hoffman SC, Comstock GW, Klag MJ, Coresh J. Risk factors for chronic kidney disease: a prospective study of 23,534 men and women in Washington County, Maryland. J Am Soc Nephrol. 2003;14:2934-2941. 40. Kern EFO, Maney M, Miller DR, et al. Failure of ICD-9-CM codes to identify patients with comorbid chronic kidney disease in diabetes. Health Serv Res. 2005;41(2):564-580. 41. Li SQ, Cunningham J, Cass A. Renal-related deaths in Australia 1997-1999. Intern Med J. 2004;34:259-265. 42. Oliver MJ, Lok CE, Shi J, Rothwell DM. Dialysis therapy for persons with diabetes: In Hux JE, Booth GL, Slaughter PM, Laupacis A (eds). Diabetes in Ontario: An ICES Practice Atlas: Institute for Clinical Evaluative Sciences 2003:8.165-8.180. 43. Brameld KJ, Thomas MAB, Holman CD, Bass AJ, Rouse IL. Validation of linked administrative data on end-stage renal failure: application of record linkage to a clinical base population. Aust N Z J Public Health. 1999;23(5):464-467. Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 49
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Appendix A: DCPNS Physician Referral Form APPENDIX A DCPNS PHYSICIAN REFERRAL FORM Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 51
Appendix A: DCPNS Physician Referral Form 52 Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010
Appendix A: DCPNS Physician Referral Form Quantifying the Burden of Diabetes in Nova Scotia Diabetes Care Program of Nova Scotia 2010 53