Osteoarthritis: a comorbid marker for longer life?

Probabilistic Quantification of Bias to Combine the Strengths of Population-Based Register Data and Clinical Cohorts-Studying Mortality in Osteoarthritis

We propose combining population-based register data with a nested clinical cohort to correct misclassification and unmeasured confounding through probabilistic quantification of bias. We have illustrated this approach by estimating the association between knee osteoarthritis and mortality. We used the Swedish Population Register to include all persons resident in the Skåne region in 2008 and assessed whether they had osteoarthritis using data from the Skåne Healthcare Register. We studied mortality through year 2017 by estimating hazard ratios. We used data from the Malmö Osteoarthritis Study (MOA), a small cohort study from Skåne, to derive bias parameters for probabilistic quantification of bias, to correct the hazard ratio estimate for differential misclassification of the knee osteoarthritis diagnosis and confounding from unmeasured obesity. We included 292,000 persons in the Skåne population and 1,419 from the MOA study. The adjusted association of knee osteoarthritis with all-cause mortality in the MOA sample had a hazard ratio of 1.10 (95% confidence interval (CI): 0.80, 1.52) and was thus inconclusive. The naive association in the Skåne population had a hazard ratio of 0.95 (95% CI: 0.93, 0.98), while the bias-corrected estimate was 1.02 (95% CI: 0.59, 1.52), suggesting high uncertainty in bias correction. Combining population-based register data with clinical cohorts provides more information than using either data source separately.

Increased lifespan, decreased mortality, and delayed cognitive decline in osteoarthritis

In absence of therapies targeting symptomatic dementia, better understanding of the biology underlying a cognitive decline is warranted. Here we present the results of a meta-analysis of the impact of osteoarthritis (OA) on cognitive decline and overall mortality. Across 7 independent datasets obtained in studies of populations in the USA, EU and Australia (NBER, NSHAP, TILDA, NACC, Kaiser Permanente, GRIM BOOKS, OAI, with a total of >7 × 10⁷ profiles), OA cohorts demonstrated higher cognitive scores, later dementia onset as well as longer lifespan and lower age-specific all-cause mortality. Moreover, generalized OA with multiple localizations is associated with more significant reduction of mortality and dementia than a singly localized OA or no arthritis. In OA patients with younger ages, all-cause mortality was disproportionally reduced as compared to that in controls, while exponential term of Gompert’z hazard function was increased, accelerating mortality accrual at later ages. Up to 8–10% of poly-osteoarthritic patients are predicted and observed to reach centenarian lifespan, while in matched non-OA population the same benchmark is reached by less than 1% of patients. These results point at a possibility of life-extending and cognition preserving impacts of OA-conditioned immune system.

Cause-specific mortality in osteoarthritis of peripheral joints

PURPOSE

To estimate cause-specific mortality in osteoarthritis patients compared to the general population.

METHODS

We identified all residents in southern Sweden aged 45-84 years in 2003. Through the Skåne Healthcare Register (SHR) we identified those diagnosed with osteoarthritis in peripheral joints between 1998 and 2003. We followed all residents from 2004 until relocation outside of the region, death, or end of 2014. We classified the underlying cause of death from death certificates into: cardiovascular and neoplasms, diabetes, infections, dementia, diseases of digestive system, or other causes. For estimation, we used multi-state adjusted Cox proportional hazards models.

RESULTS

We identified 15,901 patients (mean age [SD] 67 years [10], 41% men) with prevalent doctor-diagnosed osteoarthritis in knee, 9347 in hip, 4004 in hand and 5447 in other peripheral joints among 469,177 residents. For most causes of death in osteoarthritis patients, we found no increased mortality, with hazard ratios (HRs) close to 1, similar for men and women. However, for knee and hip osteoarthritis and cardiovascular death, HRs were non proportional and increased to 1.19 (95%CI 1.10, 1.28) and 1.13 (1.03, 1.24) during 9-11 years of follow-up, mostly due to excess mortality from chronic ischemic heart diseases and heart failure.

CONCLUSIONS

The risk of cardiovascular excess deaths increases with duration of knee and hip osteoarthritis. The major contributors are chronic ischemic heart diseases and heart failure. Our results call for improved implementation of osteoarthritis treatment guidelines, with major focus on interventions to address mobility limitations and maintaining or increase physical activity level.

Using Information on Patient Adherence to Antipsychotic Medication to Understand Their Adherence to Other Medications

PURPOSE

To assess how patient adherence to atypical antipsychotic medications is associated with adherence to concurrently used medications that treat other serious mental illnesses (SMIs), type-2 diabetes, or hypertension.

METHODS

Among patients who had been diagnosed with an SMI (i.e., bipolar disorder, major depressive disorder, or schizophrenia) in the previous year, we used health-insurance claims data to measure adherence based on medication fills. Patients diagnosed with an SMI were required to have 1) a prescription for an atypical oral antipsychotic, and 2) another SMI therapy or oral anti-diabetic or antihypertensive agent in the same year. The patient's concurrent adherence to an antipsychotic and one of 23 other medications was measured by the proportion of days covered (PDC) over a one-year period. Patients were considered adherent when the PDC was ≥ 80%. The strength of the association between their atypical antipsychotic adherence and their concurrent medication adherence was evaluated using the following metrics: accuracy, positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

The average (standard deviation) age of patients (N = 129,614) was 44.8 (14.8) years and 62.2% of patients were female. The median accuracy based on atypical antipsychotic adherence to the other 23 medications was 67% (range, 55-71%; statistically different from 50% accuracy in all cases, P < 0.001). Accuracy was higher than physician predictions of adherence from previous studies (53%). The negative predictive value of antipsychotic adherence (75%; range, 62-88%) was generally higher than the PPV (62%; range, 43-67%; all, P < 0.001).

CONCLUSION

Information on patient adherence to antipsychotics provides significant insight into adherence to other medications often used by patients with SMI. Because NPV is higher than PPV, adherence to antipsychotics is likely to be a necessary but not sufficient condition for patients with SMI regarding adherence to non-SMI medications.

Medication Adherence Patterns Among Patients with Multiple Serious Mental and Physical Illnesses

INTRODUCTION

Patients with mental and physical health conditions are complex to treat and often use multiple medications. It is unclear how adherence to one medication predicts adherence to others. A predictive relationship could permit less expensive adherence monitoring if overall adherence could be predicted through tracking a single medication.

METHODS

To test this hypothesis, we examined whether patients with multiple mental and physical illnesses have similar adherence trajectories across medications. Specifically, we conducted a retrospective cohort analysis using health insurance claims data for enrollees who were diagnosed with a serious mental illness, initiated an atypical antipsychotic, as well as an SSRI (to treat serious mental illness), biguanides (to treat type 2 diabetes), or an ACE inhibitor (to treat hypertension). Using group-based trajectory modeling, we estimated adherence patterns based on monthly estimates of the proportion of days covered with each medication. We measured the predictive value of the atypical antipsychotic trajectories to adherence predictions based on patient characteristics and assessed their relative strength with the R-squared goodness of fit metric.

RESULTS

Within our sample of 431,591 patients, four trajectory groups were observed: non-adherent, gradual discontinuation, stop-start, and adherent. The accuracy of atypical antipsychotic adherence for predicting adherence to ACE inhibitors, biguanides, and SSRIs was 44.5, 44.5, and 49.6%, respectively (all p < 0.001 vs. random). We also found that information on patient adherence patterns to atypical antipsychotics was a better predictor of patient adherence to these three medications than would be the case using patient demographic and clinical characteristics alone.

CONCLUSION

Among patients with multiple chronic mental and physical illnesses, patterns of atypical antipsychotic adherence were useful predictors of adherence patterns to a patient's adherence to ACE inhibitors, biguanides, and SSRIs.

FUNDING

Otsuka Pharmaceutical Development & Commercialization, Inc.

Prevalence of osteoarthritis in individuals with COPD: a systematic review

The objective of this review was to examine the prevalence of osteoarthritis (OA) in individuals with COPD. A computer-based literature search of CINAHL, Medline, PsycINFO and Embase databases was performed. Studies reporting the prevalence of OA among a cohort of individuals with COPD were included. The sample size varied across the studies from 27 to 52,643 with a total number of 101,399 individuals with COPD recruited from different countries. The mean age ranged from 59 to 76 years. The prevalence rates of OA among individuals with COPD were calculated as weighted means. A total of 14 studies met the inclusion criteria with a prevalence ranging from 12% to 74% and an overall weighted mean of 35.5%. Our findings suggest that the prevalence of OA is high among individuals with COPD and should be considered when developing and applying interventions in this population.

Osteoarthritis-patterns, cardio-metabolic risk factors and risk of all-cause mortality: 20 years follow-up in patients after hip or knee replacement

Osteoarthritis (OA) is a common musculoskeletal disorder and occur in different patterns. However, its impact on long-term all-cause-mortality is inconclusive. Study aims: Investigate 20-year all-cause-mortality in patients with hip/knee arthroplasty (recruited 1995/1996, N = 809) from the Ulm Osteoarthritis Study-cohort, in comparison to general population. Furthermore, to enlighten the triangle between baseline life-style and cardio-metabolic risk factors, phenotypic OA-patterns (laterality, generalization, cause) and all-cause-mortality. Mortality was assessed during 20 years follow-up. Standardized mortality ratios (SMR), adjusted odds ratios and hazard ratios (aHR) were calculated. After five years cohort-mortality was reduced compared to the general population, however 20 years later assimilated (SMR = 1.11; 95%-CI 0.73-1.49). OA-patterns were associated with age, cholesterol, and overweight/obesity. In comparison to primary OA decreased mortality was observed for patients with secondary OA (aHR = 0.76; 95%-CI 0.61-0.95) adjusted for age, smoking, overweight/obesity, diabetes, hypertension, cardiac insufficiency, uric acid, and lower cholesterol. There was no increased mortality in patients after 20 years follow-up compared to general population. Significantly decreased mortality in secondary compared to primary OA suggests a subtype-specific involvement of systemic co-factors in determination of all-cause-mortality. Because cardio-metabolic risk factors were associated with increased risk of bilateral OA and lower long-term survival, those risk factors should be consequently targeted in OA-patients.

All-cause Mortality in Knee and Hip Osteoarthritis and Rheumatoid Arthritis

BACKGROUND

While increased mortality in rheumatoid arthritis (RA) is well established, there is conflicting evidence on the association between osteoarthritis (OA) and mortality. Our aim was to estimate all-cause mortality in Swedish patients with RA and OA compared with the general population.

METHODS

Cohort study of the population of Skåne region, Sweden (1.3 million), based on physicians' diagnostic codes in a mandatory register covering all health care. We included all subjects aged ≥45 years who between 1998 and 2012 consulted any physician at least once. We identified those who received a diagnosis of RA, knee OA, or hip OA. We followed all subjects until death, relocation outside Skåne region, or end of 2013, and analyzed data using Cox proportional hazard regression with attained age as time scale.

RESULTS

We identified 8,067 patients with RA, 51,939 with knee OA and 29,442 with hip OA among 524,136 in the population aged ≥45 years. The mortality rates adjusted for sex, socioeconomic status, and comorbidities were elevated for RA, hazard ratio 1.86 (95% confidence interval = 1.78, 1.94) but not in knee or hip OA compared with the general population seeking health care, hazard ratio 0.87 (0.85, 0.89) and 0.90 (0.87, 0.92), respectively. Extensive sensitivity analyses supported the conclusion of no increased mortality in OA.

CONCLUSIONS

In Sweden, RA is associated with about doubled mortality rate, but we found no increased mortality in patients with knee and hip OA. Possible selection of those seeking physician care for knee or hip pain and/or OA management in health care are plausible explanations.

Systematic review of the impact of osteoarthritis on health outcomes for comorbid disease in older people

OBJECTIVE

A systematic review was undertaken examining the impact of comorbid osteoarthritis on health outcomes for people aged 50 years or older with cardiovascular disease, diabetes or obesity.

DESIGN

The protocol is registered in PROSPERO (CRD42015023417). Relevant electronic databases and grey literature were systematically searched for studies published in English between January 2005 and December 2016. Two reviewers independently screened studies for selection using predetermined inclusion and exclusion criteria, and independently completed methodological quality review. Data was extracted at study level by one reviewer and independently checked by a second reviewer, using a standardized form. The results across studies were qualitatively synthesized with outcomes described and summarized.

RESULTS

Of 1456 articles, we identified 15 relevant studies, with nine good to high quality studies describing significant negative impact of osteoarthritis on outcomes for cardiovascular diseases. There were too few studies focussing on diabetes and obesity to make conclusions in regard to these diseases.

CONCLUSIONS

This review provides evidence that osteoarthritis should not be overlooked when impacts of chronic disease on health outcomes and related health service use are considered. There is a clear need for more studies that consider the impacts of osteoarthritis on comorbid disease, especially those that consider the impact of osteoarthritis beyond the morbidity impacts. The management of comorbid osteoarthritis should be addressed for those with cardiovascular disease, and treatment choices considered given this association.

Assessing the extent of drug interactions among patients with multimorbidity in primary and secondary care in the West Midlands (UK): a study protocol for the Mixed Methods Multimorbidity Study (MiMMS)

INTRODUCTION

The numbers of patients with three or more chronic conditions (multimorbidity) are increasing, and will rise to 2.9 million by 2018 in the UK alone. Currently in the UK, conditions are mainly managed using over 250 sets of single-condition guidance, which has the potential to generate conflicting recommendations for lifestyle and concurrent medication for individual patients with more than one condition. To address some of these issues, we are developing a new computer-based tool to help manage these patients more effectively. For this tool to be applicable and relevant to current practice, we must first better understand how existing patients with multimorbidity are being managed, particularly relating to concerns over prescribing and potential polypharmacy.

METHODS AND ANALYSIS

Up to four secondary care centres, two community pharmacies and between four and eight primary care centres in the West Midlands will be recruited. Interviewees will be purposively sampled from these sites, up to a maximum of 30. In this mixed methods study, we will perform a dual framework analysis on the qualitative data; the first analysis will use the Theoretical Domains Framework to assess barriers and enablers for healthcare professionals around the management of multimorbid patients; the second analysis will use Normalisation Process Theory to understand how interventions are currently being successfully implemented in both settings. We will also extract quantitative anonymised patient data from primary care to determine the extent of polypharmacy currently present for patients with multimorbidity in the West Midlands.

DISCUSSION

We aim to combine these data so that we can build a useful, fully implementable tool which addresses the barriers most amenable to change within both primary and secondary care contexts.

ETHICS AND DISSEMINATION

Favourable ethical approval has been granted by The University of Birmingham Research Ethics Committee (ERN_16-0074) on 17 May 2016. Our work will be disseminated through peer-reviewed literature, trade journals and conferences. We will also use the dedicated web page hosted by the University to serve as a central point of contact and as a repository of our findings. We aim to produce a minimum of three articles from this work to contribute to the international scientific literature.

PROTOCOL REGISTRATION NUMBER

NIHR Clinical Research Network Portfolio Registration CPMS ID 30613.

Patterns of Adherence to Oral Atypical Antipsychotics Among Patients Diagnosed with Schizophrenia

BACKGROUND

Poor medication adherence contributes to negative treatment response, symptom relapse, and hospitalizations in schizophrenia. Many health plans use claims-based measures like medication possession ratios or proportion of days covered (PDC) to measure patient adherence to antipsychotics. Classifying patients solely on the basis of a single average PDC measure, however, may mask clinically meaningful variations over time in how patients arrive at an average PDC level.

OBJECTIVE

To model patterns of medication adherence evolving over time for patients with schizophrenia who initiated treatment with an oral atypical antipsychotic and, based on these patterns, to identify groups of patients with different adherence behaviors.

METHODS

We analyzed health insurance claims for patients aged ≥ 18 years with schizophrenia and newly prescribed oral atypical antipsychotics in 2007-2013 from 3 U.S. insurance claims databases: Truven MarketScan (Medicaid and commercial) and Humana (Medicare). Group-based trajectory modeling (GBTM) was used to stratify patients into groups with distinct trends in adherence and to estimate trends for each group. The response variable was the probability of adherence (defined as PDC ≥ 80%) in each 30-day period after the patient initiated antipsychotic therapy. GBTM proceeds from the premise that there are multiple distinct adherence groups. Patient demographics, health status characteristics, and health care resource use metrics were used to identify differences in patient populations across adherence trajectory groups.

RESULTS

Among the 29,607 patients who met the inclusion criteria, 6 distinct adherence trajectory groups emerged from the data: adherent (33%); gradual discontinuation after 3 months (15%), 6 months (7%), and 9 months (5%); stop-start after 6 months (15%); and immediate discontinuation (25%). Compared to patients 18-24 years of age in the adherent group, patients displaying a stop-start pattern after 6 months had greater odds of having a history of drug abuse (OR = 1.46; 95% CI = 1.26-1.66; P < 0.001), alcohol abuse (OR = 1.34; 95% CI = 1.14-1.53; P< 0.001), and a codiagnosis of major depressive disorder (OR = 1.24; 95% CI = 1.05-1.44; P < 0.001) and were less likely to be aged 35-54 years (OR = 0.66; 95% CI = 0.46-0.85; P < 0.001).

CONCLUSIONS

Longitudinal medication adherence patterns can be expressed as distinct trajectories associated with specific patient characteristics and health care utilization patterns. We found 6 distinct patterns of adherence to antipsychotics over 12 months. Patients in different groups may warrant different types of clinical interventions to prevent hospitalizations, longer hospital stays, and increased clinical complexity. For example, clinicians may consider regular home visits, assertive community treatment, and other related interventions for patients at high risk of immediate discontinuation. Health plans should consider supplementing claims-based adherence measures with new technologies that are able to track patient adherence patterns over time.

DISCLOSURES

Otsuka Pharmaceutical Development & Commercialization provided support for this research. MacEwan and Shafrin are employees of Precision Health Economics, which was contracted by Otsuka Pharmaceutical Development & Commercialization to conduct this study. Lakdawalla is the Chief Scientific Officer and a founding partner of Precision Health Economics. Forma is an employee of Otsuka Pharmaceutical Development & Commercialization. Hatch is a former employee of Otsuka Pharmaceutical Development & Commercialization and is a current employee of ODH, Inc. Lindenmayer has received grant/research support from Janssen, Lilly, AstraZeneca, Johnson & Johnson, Pfizer, BMS, Otsuka, Dainippon, and Roche and is a consultant for Janssen, Lilly, Merck, Shire, and Lundbeck. Portions of this study were presented as a poster at the American Society of Clinical Psychopharmacology Annual Meeting in Miami Beach, Florida; June 23, 2015; and at the 28th Annual U.S. Psychiatric and Mental Health Congress; San Diego, California; September 12, 2015. Study concept and design were contributed by Forma, Ladkawalla, MacEwan, and Shafrin, along with Hatch and Lindenmayer. MacEwan, Shafrin, Forma, and Lakdawalla collected the data, along with Hatch and Lindenmayer. Data interpretation was performed by Hatch, Lindenmayer, MacEwan, and Shafrin, assisted by Forma and Lakdawalla. The manuscript was written and revised by MacEwan, Forma, and Shafrin, along with Hatch Lakdawalla, and Lindenmayer.

A systematic review of validated methods for identifying patients with rheumatoid arthritis using administrative or claims data

PURPOSE

To review the evidence supporting the validity of billing, procedural, or diagnosis code, or pharmacy claim-based algorithms used to identify patients with rheumatoid arthritis (RA) in administrative and claim databases.

METHODS

We searched the MEDLINE database from 1991 to September 2012 using controlled vocabulary and key terms related to RA and reference lists of included studies were searched. Two investigators independently assessed the full text of studies against pre-determined inclusion criteria and extracted the data. Data collected included participant and algorithm characteristics.

RESULTS

Nine studies reported validation of computer algorithms based on International Classification of Diseases (ICD) codes with or without free-text, medication use, laboratory data and the need for a diagnosis by a rheumatologist. These studies yielded positive predictive values (PPV) ranging from 34 to 97% to identify patients with RA. Higher PPVs were obtained with the use of at least two ICD and/or procedure codes (ICD-9 code 714 and others), the requirement of a prescription of a medication used to treat RA, or requirement of participation of a rheumatologist in patient care. For example, the PPV increased from 66 to 97% when the use of disease-modifying antirheumatic drugs and the presence of a positive rheumatoid factor were required.

CONCLUSIONS

There have been substantial efforts to propose and validate algorithms to identify patients with RA in automated databases. Algorithms that include more than one code and incorporate medications or laboratory data and/or required a diagnosis by a rheumatologist may increase the PPV.

Do musculoskeletal degenerative diseases affect mortality and cause of death after 10 years in Japan?

There are several reports from Europe and the United States on mortality from musculoskeletal degenerative diseases; however, no reports have been published from Japan. This study is the first that has examined whether musculoskeletal degenerative diseases affect life prognosis in Japan. As many as 944 persons who were 60 years of age and older and who underwent one or more musculoskeletal checkups (knee, lower back, and bone mineral density examination) were enrolled. Survival and death after 10 years were examined. For each knee, lower back, and bone mineral density examination, subjects were divided into normal and abnormal groups. For each of the examinations (knee, lower back, or bone mineral density), 10-year mortality was compared between the two groups. Also, causes of death were examined after 10 years. As many as 805 subjects survived and 125 died. For those with and without osteoarthritis of the knee, mortality after 10 years was 17 and 10%, respectively. For those with and without lower back abnormalities, mortality after 10 years was 12 and 14%, respectively. For those with or without low bone mineral density, mortality after 10 years was 17 and 10%, respectively. Multivariate analysis adjusted for age, gender, body mass index, and lifestyle revealed that odds ratio of death after 10 years was 2.32 and 2.33 in the presence of osteoarthritis of the knee and a low bone mineral density, respectively, and thus the risk of death after 10 years was significantly high. With regard to the cause of death, cerebrovascular and cardiovascular diseases were most frequently evident in patients with osteoarthritis of the knee. Musculoskeletal degenerative diseases influence mortality after 10 years.

Risk for death associated with medications for recently diagnosed chronic obstructive pulmonary disease

BACKGROUND

Concerns exist regarding increased risk for mortality associated with some chronic obstructive pulmonary disease (COPD) medications.

OBJECTIVE

To examine the association between various respiratory medications and risk for death in veterans with newly diagnosed COPD.

DESIGN

Nested case-control study in a cohort identified between 1 October 1999 and 30 September 2003 and followed through 30 September 2004 by using National Veterans Affairs inpatient, outpatient, pharmacy, and mortality databases; Centers for Medicare & Medicaid Services databases; and National Death Index Plus data. Cause of death was ascertained for a random sample of 40% of those who died during follow-up. Case patients were categorized on the basis of all-cause, respiratory, or cardiovascular death. Mortality risk associated with medications was assessed by using conditional logistic regression adjusted for comorbid conditions, health care use, and markers of COPD severity.

SETTING

U.S. Veterans Health Administration health care system.

PARTICIPANTS

32 130 case patients and 320 501 control participants in the all-cause mortality analysis. Of 11 897 patients with cause-of-death data, 2405 case patients had respiratory deaths and 3159 case patients had cardiovascular deaths.

MEASUREMENTS

All-cause mortality; respiratory and cardiovascular deaths; and exposure to COPD medications, inhaled corticosteroids, ipratropium, long-acting beta-agonists, and theophylline in the 6 months preceding death.

RESULTS

Adjusted odds ratios (ORs) for all-cause mortality were 0.80 (95% CI, 0.78 to 0.83) for inhaled corticosteroids, 1.11 (CI, 1.08 to 1.15) for ipratropium, 0.92 (CI, 0.88 to 0.96) for long-acting beta-agonists, and 1.05 (CI, 0.99 to 1.10) for theophylline. Ipratropium was associated with increased cardiovascular deaths (OR, 1.34 [CI, 1.22 to 1.47]), whereas inhaled corticosteroids were associated with reduced risk for cardiovascular death (OR, 0.80 [CI, 0.72 to 0.88]). Results were consistent across sensitivity analyses.

LIMITATIONS

Current smoking status and lung function were not measured. Misclassification of cause-specific mortality is unknown.

CONCLUSION

The possible association between ipratropium and elevated risk for all-cause and cardiovascular death needs further study.

Multiple chronic conditions: prevalence, health consequences, and implications for quality, care management, and costs

Persons with multiple chronic conditions are a large and growing segment of the US population. However, little is known about how chronic conditions cluster, and the ramifications of having specific combinations of chronic conditions. Clinical guidelines and disease management programs focus on single conditions, and clinical research often excludes persons with multiple chronic conditions. Understanding how conditions in combination impact the burden of disease and the costs and quality of care received is critical to improving care for the 1 in 5 Americans with multiple chronic conditions. This Medline review of publications examining somatic chronic conditions co-occurring with 1 or more additional specific chronic illness between January 2000 and March 2007 summarizes the state of our understanding of the prevalence and health challenges of multiple chronic conditions and the implications for quality, care management, and costs.