 To identify self-reported reasons for not filling a new prescription for statin therapy.

 Potential participants were identified from a randomized, controlled trial among Kaiser Permanente Southern California (KPSC) members aged >24 years with no  record of redeeming a new statin medication, defined as primary nonadherence. Among 1158 eligible patients, 98 were randomly selected and participated in a  semi-structured telephone interview that included questions on whether the respondent redeemed their statin prescription, why the patient may have chosen not to use a  KPSC pharmacy, reasons for not filling the prescription, use of non-prescription products for elevated cholesterol levels, and questions to assess health literacy.

 At 12 weeks post—index prescription date, 75% of 98 respondents reported not filling their new statin prescription, 20% reported picking it up from a non-KPSC  pharmacy, 4% had already picked up the prescription at a KPSC pharmacy, and 1% did not know if it had been filled. The 3 most commonly cited reasons for primary  nonadherence were general concerns about taking the medication (63%), a decision to try lifestyle modifications (63%), and fear of side effects (53%). A substantial proportion (33%) of respondents reported inadequate health literacy.

These data suggest the need for interventions that address patients’ negative perceptions of statins while emphasizing the benefits of statin therapy for  reducing cardiovascular morbidity and mortality in formats accessible to those with limited health literacy.

This study highlights patients’ concerns about statins and a preference for lifestyle modifications among those who do not fill their first statin prescription.

Reasons for primary nonadherence to statin therapy are multifactorial; therefore, individualized interventions may be warranted.

Further research is needed to explore patient—physician communication about statintherapy, and the most appropriate communication methods and formats for different audiences.

Cardiovascular disease (CVD) is the primary cause of death in the United States.

 Furthermore, the total estimated direct and indirect costs of CVD and stroke in the United  States were $286 billion for 2007.

 Hypercholesterolemia is a well-known risk factor for CVD; the estimated prevalence of elevated low-density lipoprotein cholesterol  (LDL-C) levels among adults in the United States aged 20 years or more was 32% in 2008.

Hydroxymethylglutaryl-coenzyme A reductase inhibitors (statins) are widely used  for management of elevated cholesterol levels and have been shown to be effective at preventing fatal and non-fatal cardiovascular events

and potentially reducing  healthcare costs

The potential public health benefits of statin use are limited if there are patients who never fill newly ordered medication (primary nonadherence). While  most of the available evidence on nonadherence to statin therapy has focused on refill rates (secondary nonadherence), recent studies have shown that primary adherence  to statin therapy is suboptimal across a variety of populations.

 For example, among a large, diverse cohort of managed care patients in Southern California, 20% of  patients failed to fill their initial statin prescription.

 An evaluation of a community-based electronic prescribing initiative found that 28% of initial prescriptions for lipid-lowering  agents were never filled.

A prospective study among military veterans given a new statin prescription found that 10% of the cohort reported having never started their medication.

In addition to measuring the prevalence of primary nonadherence to statin therapy, understanding self-reported factors that result in unclaimed prescriptions is important for developing patient-focused interventions aimed at improving adherence and ultimately reducing adverse CVD events. While previous studies  have assessed sociodemographic, medical, and healthcare utilization characteristics associated with nonadherence to statins,19 to our knowledge, only 1 published study  has explored patients’ perceptions of statin therapy that contribute to primary nonadherence.15 Three additional studies assessed patients’ perceptions of statin therapy with  respect to nonadherence but these analyses combined patients who never filled their statin prescription and patients who discontinued their medication. 14,20,21 The aim of  our study was to explore self-reported reasons for primary nonadherence among patients with a newly prescribed statin medication, thus contributing to the scant literature on this topic.

This study was conducted at Kaiser Permanente Southern California (KPSC), an integrated health delivery system which provides comprehensive care to more than 3.4million members at 14 medical centers and 197 medical offices. KPSC clinical practice guidelines for adult cholesterol management recommend statin treatment among all people with established coronary artery disease (CAD), diabetes mellitus (40 years or older), ischemic stroke or trans-ischemic stroke, abdominal aortic aneurysm,  peripheral artery disease, or carotid artery stenosis (>50%). In these patients, statins are recommended regardless of baseline LDL-C, and LDL-C goal is less than 100  mg/dL with an optional goal of less than 70 mg/dL. For patients with diabetes aged 39 years or under, patients with chronic kidney disease stages 4 or 5, and those with a 10-year CAD risk greater than 20%, statins are recommended with an LDL-C goal less than 100 mg/dL. For primary prevention patients who have a 10-year CAD risk less than 20%, the LDL-C goal is less than 130 mg/dL. Simvastatin was the preferred first-line statin for both primary and secondary prevention patients within KPSCduring the study. In addition, KPSC guidelines recommend lifestyle modifications in the management of adults with dyslipidemia.

The sample for this study was  derived from KPSC members enrolled in a randomized controlled trial evaluating an automated system to increase adherence to newly prescribed statins using telephone  messaging and follow-up letters. The trial’s inclusion criteria are described in detail elsewhere.

 In brief, KPSC members were eligible for the trial if they were at least 24 years of age, had a new statin prescription that had not been filled at a KPSC pharmacy within 1 to 2 weeks of being ordered, had 12 months of continuous KPSC  membership prior to the statin order, and did not have a statin or statin combination drug dispensed within 365 days prior to the index  prescription date. A total of 5216 members were equally randomized to the intervention arm and a usual care arm. Members in the intervention arm received an automated telephone call followed up 1 week later by a letter for those who had not redeemed their statin medication at KPSC. Members were randomly selected for this study from  the 1158 participants in both arms of the randomized trial who had a new statin prescription ordered between May 10 and June 14, 2010, who had no record of redeeming  their statin medication 12 weeks after the prescription date and whose preferred language, according to administrative records, was English. Members could  have, however, redeemed their statin prescription between study selection and recruitment (a maximum of 5 days). Participants’ demographic characteristics were  captured through structured administrative databases. LDL-C measurements were obtained from electronic medical records closest to the date each member was  prescribed the new statin medication.

Between June 23 and July 30, 2010, we attempted to contact eligible members on a rolling basis for a brief telephone interview. Due to budget considerations, we aimed to complete 100 interviews. We made a maximum of 2 attempts over 5 days to contact each potential participant.

Two trained research staff used a survey instrument  consisting of scripted questions to assess 1) whether respondents redeemed their statin prescription, 2) why the patient may have chosen not to use a KPSC pharmacy,  3) reasons for not filling the prescription, 4) use of non-prescription products for cholesterol reduction, and 5) respondents’ health literacy (

). To explore factors  that may have contributed to primary nonadherence, interviewers read a series of statements derived from the published literature

 about concerns with side effects, safety, effectiveness, and affordability, and asked respondents to indicate whether or not (yes/no) each reason applied to them. Responses to open-ended questions were recorded verbatim. Poor health literacy has been associated with low medication adherence,

therefore we measured self-reported health literacy using a previously validated 3-item instrument that assesses problems due to reading, understanding, and filling out medical forms.

 The study protocol was approved by the  Institutional Review Board of Kaiser Permanente Southern California and informed consent was obtained by the telephone interviewer prior to the start of each interview.

Summary statistics (means and proportions) were calculated for demographic characteristics (age, gender, race/ethnicity, education, and income), LDL-C, redemption of statin prescription, reasons for nonadherence, and use of non-prescription products to lower cholesterol. Responses to openended questions about reasons for primary  nonadherence were reported qualitatively.

Responses to each of the validated health literacy screening questions were scored on a scale of 1 to 5 and summed to create  an overall score that ranged from 1 to 15, with higher values representing better health literacy.

 The overall health literacy score was dichotomized as “adequate”  (score = 15), defined as the respondent reporting no problems, and “inadequate” (score 

 All analyses were performed using SAS statistical software version 9.2  (SAS Institute, Cary, North Carolina).

Among 1158 members eligible for interview, 23 were excluded during recruitment: 8 did not speak fluent English, 7 had a non-working telephone number, 5 were physically or mentally incapacitated, 2 had the statin prescription canceled by their physician, and 1 was deceased (

). We telephoned 379 eligible members, making 120 contacts. Of the 120 contacts, 22 refused to participate and 98 completed an interview. The overall response rate was 81.7%.

Demographic and clinical characteristics of the participants are provided in 

. The mean age among all survey respondents was 59.3 years (range: 29-97 years) and 46.9% were female. Nearly half of respondents were white, the large majority had at least a high school diploma, and approximately one-third had an annual household income of $50,000 or less. The mean (SD) LDL-C level closest to the date of enrollment in the randomized trial was 151 (36) mg/dL. T

welve weeks post—index date, 74.5% of respondents reported that they  had not filled their statin prescription, while 20.4% reported filling the prescription at a non-KPSC pharmacy. A small proportion of respondents claimed that they filled the  statin prescription at a KPSC pharmacy or did not know whether the prescription was filled (

). Among the 73 respondents who reported not filling their statin  prescription at any pharmacy, the most commonly cited reasons for not filling the prescription were general concerns about taking the medication (63.0%), a decision to try lifestyle modifications, such as diet and exercise, instead of taking the medication (63.0%), and  fear of side effects (53.4%) (

). Thirty-nine percent of respondents perceived the statin medication as unnecessary while 34.7% did not believe their condition to be  life-threatening. The same proportion of respondents were concerned about drug interactions (16.4%) and perceived they already took too many medications and did not  want to take any more (16.4%). Financial hardship was cited by 12.3% of respondents. When respondents were asked to qualitatively identify additional reasons they did  not pick up their statin medication, 9 reported not being aware their physician prescribed the medication, 6 had a previous supply of the medication (>365 days old), 6   preferred to take a “natural product,” and 3 did not like taking medication. One-third of respondents who left their statin prescription unfilled reported taking non-prescription  products, including supplements or herbs, to lower their cholesterol.

Among the 20 respondents who reported obtaining their statin prescription at a non-KPSC pharmacy, 8 did not have a KPSC pharmacy benefit, 5 generally purchased their prescriptions from an outside pharmacy (non-specific reason), 5 had a pharmacy benefit through another provider (eg, Veterans Affairs, Indian Health Service, workers’  compensation), and 2 preferred a non-formulary product (data not shown).

Overall, 32.9% of respondents reported inadequate health literacy. More specifically, 16.9% reported needing help reading medical material, 17.1% reported having problems learning about their medical condition, and 29.6% were not confident completing health forms alone (data not shown).

Most respondents in our study who were nonadherent with their initial statin prescription had general concerns about the medication and a preference for lifestyle modifications. To a lesser extent, respondents expressed concerns about side effects, drug interactions, and polypharmacy, and did not perceive a need for statin therapy. Cost of the statin prescription was not reported as a primary factor for respondents’ failure to redeem their prescription.

Interestingly, general concerns and a decision to try diet and exercise instead of taking statin therapy were each reported by the same proportion of respondents. The former reason may have facilitated respondents’ decision to take an alternative approach to reducing their cholesterol level, including the use of non-prescription products. Despite the concerns about adverse effects of statin therapy, the evidence among people with preexisting CVD suggests that any possible negative outcomes are outweighed by the benefits of treatment

 The findings from this study regarding safety concerns and a preference for lifestyle modification are similar to other published assessments of self-reported  factors that contribute to primary nonadherence to statin therapy. For example, a study that explored beliefs about diet control found that 79% of patients preferred to change their diet before taking a statin compared with 63% in our sample.

 Among participants of an Internet-based study who self-identified as not having filled a new statin prescription, 65% and 43% reported fear of side effects and general concerns about taking the medication, respectively.

 While 44% of respondents in that study perceived cost as a barrier to filling their statin prescription, only 12% of primary nonadherent participants in our study held this perception. This difference could be influenced by the fact that more than 90% of KPSC members have a pharmacy benefit that covers all or a large portion of medication costs.

The majority of respondents in our study who redeemed their prescription at a non-KPSC pharmacy did not have a KPSC drug benefit. This finding suggests that some patients without a pharmacy benefit may actually redeem their statin prescription, particularly if they perceive a need for the medication.

 Moreover, studies relying solely on electronic medical records to assess primary nonadherence should exclude patients without a drug benefit to avoid potentially  overestimating prevalence of primary nonadherence.

A small but noteworthy number of respondents reported not being aware of their physician having prescribed the statin medication, which suggests a need for improved patient—physician communication. At least 4 published studies of self-reported reasons for primary nonadherence to medications have found a similar experience.

 These studies analyzed prescriptions electronically transmitted to the pharmacy, which is also the primary  method of ordering prescriptions utilized by our health plan. In health systems where prescriptions are ordered electronically, providers may be able to  improve primary nonadherence by giving patients verbal and written information about the statin prescription that was ordered.

One-third of  respondents in our study had inadequate health literacy. This finding is somewhat surprising given the relatively high income and education levels of  the respondents and because we only included English speakers in the sample. Using the same 3-item instrument, a study with a large, ethnically  diverse cohort of diabetes patients in Northern California found that 62% of enrollees reported inadequate health literacy.

 With socioeconomically diverse health plan memberships, clinicians and pharmacists should consider employing low-literacy, pictorial and audiovisual education materials to  decrease primary nonadherence to statin therapy.

Our study has several limitations. First, self-reported data are subject to social desirability bias. For example, respondents may have over-reported their choice to make lifestyle changes or to report a lapse in memory rather than admit that they did not follow the physician’s advice. Second, our small  sample size and study design did not allow for meaningful statistical comparisons. Third, although KPSC membership is socioeconomically diverse,  we only sampled English speakers of 1 integrated health plan and in 1 geographic region, thus the results may differ from those in other regions and  other types of managed care organizations. Fourth, we did not directly measure health literacy, nor did we assess the relationship between health  literacy and lipid management. The main strengths of our study are the focus on primary nonadherence to statin therapy and the use of self-reported data. Only 2 of the 4 previously published studies that assessed self-reported reasons for nonadherence to statin therapy exclusively analyzed patients  who did not fill their prescription.

 Furthermore, most studies have relied on medical records and pharmacy data rather than self-reported barriers  to primary nonadherence. Our study also provided respondents with the opportunity to qualitatively cite reasons for not redeeming their prescription,  which allowed us to explore potentially unidentified self-reported reasons for primary nonadherence.

Respondents’ reasons for primary nonadherence  to statin therapy are multifactorial; therefore, individualized interventions aimed at improving primary nonadherence may be warranted. For example, it may be helpful to institute interventions at the time of the initial prescription that address patients’ negative perceptions of statins while  emphasizing the benefits of statin therapy for reducing cardiovascular morbidity and mortality. A variety of methods, formats, and styles should be  explored to help tailor patient—physician communication for different audiences. These interventions and methods should be examined in a larger  population and across different health plan types to ensure the greatest impact.The authors would like to thank the Kaiser Permanente Southern California outreach team for their support in the implementation of this study,Amy Liu for programming support, and Britta Amundsen for data collection support. They would also like to thank Colleen McHorney at Merck and Co, Inc, for expert guidance.

 Department of Research and Evaluation (TH, SFD, VC, KR), Kaiser Permanente Southern California, Pasadena, CA; Pharmacy Analytical Service (TCC, SSV), Kaiser Permanente Southern California, Downey, CA; Clinical Operations (KG), Southern California Permanente Medical Group, Pasadena, CA; Global Health Outcomes (KT), Merck Sharp and Dohme Corp (EM), Whitehouse Station, NJ; West Los Angeles Medical Center (RDS), Southern  California Permanente Medical Group, Los Angeles,CA.

This research was funded by Merck Sharp and Dohme Corp, a subsidiary of Merck and Co, Inc, Whitehouse Station, NJ.

Articles

WEB EXCLUSIVE

This study explores self-reported reasons for primary nonadherence among patients newly prescribed statin medication in an integrated health delivery system.

Primary Nonadherence to Statin Therapy: Patients' Perceptions

 Childbirth is the leading reason for hospitalization in the United States, and maternityrelated expenditures are substantial for many health insurance programs, including Medicaid. We studied the relationship between primary payer and trends in hospital-based childbirth care.

 Retrospective analysis of hospital discharge data from the Nationwide Inpatient Sample (NIS) of the Healthcare Cost and Utilization Project, a 20% stratified sample of US hospitals.

Data on 6,717,486 hospital-based births for the years 2002 through 2009 came from the NIS. We used generalized estimating equations to measure  associations over time between primary payer (Medicaid, private insurance, or self) and cesarean delivery, vaginal birth after cesarean (VBAC), labor induction,  and episiotomy.

 Controlling for clinical, demographic, and hospital factors, births covered by Medicaid had lower odds of cesarean delivery (adjusted odds ratio [AOR],  0.91), labor induction (AOR, 0.73), and episiotomy (AOR, 0.62) and higher odds of VBAC (AOR, 1.20; P <.001 for all AORs) compared with privately insured  births. Cesarean rates increased 6% annually among births paid by private insurance (AOR, 1.06; P <.001) and less rapidly (5% annually) among those covered  by Medicaid.

 US hospital-based births covered by private insurance were associated with higher rates of obstetric intervention than births paid for by Medicaid.  After controlling for clinical, demographic, and hospital factors, cesarean delivery rates increased more rapidly among births covered by private insurance,  compared with Medicaid. Changes in insurance coverage associated with healthcare reform may impact costs and quality of care for women giving birth in US  ospitals.

We studied the relationship between primary payer and trends in hospital-based childbirth care from 2002 to 2009 and found the following:

		Obstetric intervention rates increased over time for all births, regardless of payer.

		Presence and type of health insurance affected hospital-based childbirth care; births covered by private insurance had higher rates of obstetric intervention compared with Medicaid-funded births.

		Controlling for individual and hospital-level factors, the cesarean delivery rate increased more rapidly for births covered by private insurance, compared with Medicaid.

		Changes in health insurance coverage associated with the Affordable Care Act may have important health implications for women giving birth in US hospitals.

Childbirth is the leading reason for hospitalization of women in the United States,

 and hospital-based maternity care has undergone marked changes in recent years. Cesarean delivery rates have increased from 20.7% in 1996 to 32.9% in 2009.

 Rates of induction of labor have also increased, from 9.5% in 1990 to 23.1% in 2008.

 Meanwhile, rates of vaginal birth after cesarean (VBAC) have decreased from 28.3% in 1996 to 8.5% a decade later.

These changes have catalyzed interprofessional dialogue on rising rates of obstetric intervention, especially because these changes have occurred alongside increases in  adverse birth outcomes and persistent racial/ethnic disparities in maternal and neonatal health.

 Although advances in obstetric care have historically improved outcomes for mothers and babies, higher-than-expected risk-adjusted cesarean delivery rates are not associated with health gains, and high procedure intensity comes at a cost to women, infants, and the healthcare system.

Maternity and newborn care is the top expenditure category for hospital payments  by Medicaid and private insurers alike,

and costs of childbirth care have been increasing. The average facility charge for a vaginal delivery in 2004 was $7772, and this increased to $9617 by 2009. Facilities charge more for a cesarean delivery, on average, $15,779 in 2009, which was up from $12,223 in 2004.

Health insurance may impact childbirth-related healthcare such as cesarean delivery through benefits coverage, payment structures, and provider  networks.

 State-level analyses have indicated that privately insured women experience higher rates of cesarean delivery, including elective cesarean  delivery, compared with uninsured and publicly insured women.

In 2009, private insurers paid $3.8 billion for 52% of all cesarean births in US hospitals.

 The public-sector role is also large. State Medicaid programs finance 45% of all US births.

 Thus, as public payers, states have significant policy leverage over obstetric practice via Medicaid coverage and benefits structures; they also have an important fiscal stake in improving the quality and value of childbirth care and associated health outcomes.

Although research and vital statistics reports have documented changes in obstetric practice,

 the role of health insurance in facilitating or mitigating  these longitudinal trends remains largely unexplored. The potential payer impact on trends in maternity care has important policy implications, given the  volume of births in the United States per year (approximately 4 million), the public sector stake in terms of costs and health outcomes, and the role of private  payers and self-insured employers in financing childbirth care.

 The goal of this study was to characterize differences in hospital-based obstetric care by  primary payer, while controlling for relevant clinical, demographic, and hospital characteristics. Our analysis focused on changes over time (2002-2009) in delivery mode  and obstetric procedures, and it measured whether these trends were changing more or less rapidly for women who gave birth without insurance coverage  and for births financed by public versus private payers in a nationally representative sample of US hospitals.

This study used data from the Nationwide Inpatient Sample (NIS) of the Healthcare Cost and Utilization Project (HCUP), from 2002 through 2009. The NIS includes hospital discharge records for all payers for inpatient care for an approximate 20% stratified sample of US community hospitals and is the only  national hospital database with discharge records for all patients, regardless of payer,

 which makes it well suited for this analysis. The quality and validity of NIS data have been previously reported, and these data have been widely used in health services research, including studies of maternity and obstetric care. 

We analyzed discharge summaries for 6,717,486 maternal hospitalizations for childbirth in US hospitals in 44 states during the period 2002 to 2009 in which the primary payer was self (N = 241,503), Medicaid (N = 2,832,321), or private insurance (N = 3,643,643). We relied on a previously validated and published method of using NIS data to identify obstetric deliveries.

Outcome variables are defined using both International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes and Clinical Classifications Software (CCS) codes, which were developed by HCUP for use with ICD-9-CM codes.

 Delivery mode outcomes were (1) cesarean delivery (ICD- 9-CM codes 740xx, 741xx, 742xx, 744xx, and 7499) and  (2) VBAC, which was calculated as a vaginal birth conditional on indication of prior cesarean delivery (CCS code 189). The low-risk cesarean delivery rate  (shown in unadjusted comparisons in 

) is calculated as the rate of cesarean delivery among women with term, singleton, vertex pregnancies, and no  prior cesarean deliveries, following the definition employed by the American Congress of Obstetricians and Gynecologists (ACOG) as closely as the data  allow.

 Secondary obstetric care outcomes included (3) induction of labor (either medical or surgical induction; ICD-9-CM codes 731 and 734) and (4) episiotomy (ICD-9-CM code 736). Insurance status was indicated by the primary payer for the childbirth hospitalization and categorized as Medicaid, private  insurance, or self.

Our analysis controlled for patient-level demographics, including maternal age and race as recorded on hospital discharge records. Inclusion of clinical  control variables is based on recommendations from ACOG and published analyses of risk-adjustment methodologies in obstetric care

; these variables  include the following: diabetes (ICD-9-CM codes 6488x and 250xx), hypertension (ICD-9-CM codes 6420x, 6421x, 6422x, 6423x, 6424x, 6425x, and 6426x),  preeclampsia (ICD-9-CM codes 6424x and 6425x), eclampsia (ICD-9-CM code 6426x), multiple gestation (ICD-9-CM code 651xx), post date pregnancy  (pregnancy exceeding 40 weeks of gestation; ICD-9-CM codes 645, 64510, 64511, 64513, and 6453), placenta complications (ICD-9-CM codes 640 and 641), malpresentation (CCS code 187), fetal disproportion (CCS code 188), preterm delivery (delivery prior to 37 weeks of gestation; ICD-9-CM codes 6442,  64420, and 64421), and prior cesarean delivery (CCS code 189). We also controlled for hospital characteristics including bed size, teaching status, and rural  versus urban location. We used the hospital bedsize categories defined by AHRQ.

 Hospital teaching status is based on information from the American  Hospital Association’s Annual Survey of Hospitals. Finally, classification of hospitals as either urban or rural was based on Core Based Statistical Area codes  from Census 2000 data.

We constructed a series of multivariable regression models, with childbirth-related maternal hospitalization as the unit of analysis, to assess the effect of health insurance status on obstetric care from 2002 through 2009. Because units (hospitalizations) were clustered within hospitals, we used generalized estimating equations (GEE) models with clustered standard errors.32 We built GEE models with a log link for each of the dichotomous outcomes: cesarean delivery, VBAC, labor induction, and episiotomy. Final GEE regression models controlled for all of the individual demographic and clinical covariates and  hospital characteristics described above and also included interaction terms between year and insurance status to test for differential annual trends in study outcomes. Our primary goal in this context was to examine whether trends (eg, rising rates of cesarean delivery) changed more or less rapidly depending on the primary payer.

In order to display time trends by insurance status, we also present results as predicted probabilities. Calculation of predicted probabilities required that we specify particular covarinate values. We based these specifications on mean covariate values (Table 1) to represent a typical childbirth-related hospitalization.The only factors that varied in the calculation of predicted probabilities were primary payer and year of childbirth. Predicted probabilities are calculated by using these covariate values and coefficients generated by the GEE regression models described above. All analyses were performed using SAS, version 9.2. The study was granted exemption from review by the University of Minnesota Institutional Review Board.

Several characteristics of childbirth-related hospitalizations changed markedly over the study period (Table 1). The age distribution of mothers giving birth in US hospitals was fairly stable, and approximately 39% of deliveries were to white mothers, 10% were to black mothers, 19% were to Hispanic mothers, and fewer than 5% were to Asian or American Indian/Alaska Native mothers and mothers of other racial groups. Information on race/ethnicity was missing for just under 25% of mothers in this analysis, but the proportion of missing data decreased almost 50% across the study period because of improved data reporting  and collection by HCUP.

 Rates of pregnancy-related complications and associated clinical conditions generally increased over the study period, with the  largest relative increases occurring in the conditions of multiple gestation and prior cesarean delivery. Fewer than 8% of births were complicated by diabetes, hypertension, preeclampsia/eclampsia, preterm or post term gestation, placenta problems, nonvertex fetal presentation (ie, breech), and fetal disproportion. The characteristics of hospitals in which births occurred remained fairly stable between 2002 and 2009, with slight decreases in births in small and rural  hospitals. On average, nearly one-half of all births occurred in teaching hospitals and 11% were in rural hospitals.

Just over one-half of all hospitalizations for  childbirth were covered by private health insurance (54.2%; 

), but that proportion decreased by 14% over the study period. In contrast, Medicaid  coverage for births rose by 21%, from 38.0% of births in 2002 to 46.0% in 2009. A small but growing percentage of hospitalizations for childbirth were not  covered by health insurance; this proportion increased from 3.4% to 3.8% of all births.

These data indicated increasing rates of cesarean delivery and labor induction and decreasing rates of VBAC and episiotomy from 2002 to 2009 (Table 2). The average overall rate of cesarean delivery was 30.9% across the  study period, while the average low-risk cesarean delivery rate was 11.2%; both increased over time. The VBAC rate decreased dramatically, from 17.6% in  2002 to 8.5% in 2009. In contrast, the rate of labor induction increased over this period, from 16.4% to 19.1%. The average rate of episiotomy was 10.7%, and it decreased over the study period.

presents regression model results which measure differential changes over time in hospital-based obstetric  care for deliveries, by primary payer. The top panel shows results for deliveries covered by health insurance compared with those where the primary payer  was self (ie, uninsured), and the bottom panel presents results for all births covered by health coverage.stimates are presented as adjusted odds ratios (AORs) with 95% confidence intervals (CIs). The first column lists the main study outcomes, the second column presents differences by payer, the third column presents change over time, and the final column presents how annual time trends differ by primary payer (on the basis of an interaction term). All analyses  controlled for the demographic, clinical, and hospital characteristics presented in Table 1.

On average, women without health insurance coverage (self-pay) were less likely than insured women to have a cesarean delivery (AOR [95% CI], 0.70  [0.69-0.72]) and more likely to have had a VBAC (1.63 [1.54-1.72]). There were significant annual increases in cesarean delivery rates (yearly AOR, 1.05)  and decreases in VBAC (0.89), but these trends did not differ based on whether the delivery was covered by insurance. Women with no insurance coverage  were less likely than insured women to have their labor induced (AOR [95% CI], 0.66 [0.65-0.68]) or to have had an episiotomy (0.89 [0.87-0.91]).

When the focus is shifted to differences among insured births according to payer, women with Medicaid coverage at the time of childbirth were less likely to have a cesarean delivery (AOR [95% CI], 0.91 [0.90-0.91]) and more likely to have a VBAC (1.20 [1.17-1.23]) after controlling for demographic, clinical, and  hospital characteristics. Rates of cesarean delivery increased 6% annually among births paid for by private insurance (AOR, 1.06; 

 <.001) and less rapidly  (5% annually) among those with Medicaid coverage (annual AOR, 0.99; 

 <.001). Rates of VBAC decreased 12% annually among births covered by private  insurance (AOR, 0.88; 

 <.001), but there was no difference in the rate of decline by payer. Women with Medicaid coverage were less likely to experience labor induction (0.73 [0.73-0.74]) or episiotomy (0.62 [0.62-0.63]). Although rates of labor induction were lower amongMedicaid beneficiaries (AOR, 0.73) compared with privately insured women, they also increased more rapidly over time for Medicaid beneficiaries (AOR, 1.03; 

 <.001) compared with privately insured women.

 presents model-based predicted probabilities of cesarean delivery during the childbirth-related hospitalization of a 26-year-old  white woman with no pregnancy complications who is giving birth at a large, urban teaching hospital. An uninsured woman’s birth would have been least  likely to involve cesarean delivery, and a birth covered by Medicaid had a lower predicted probability of cesarean delivery than the same type of birth  covered by private insurance. The predicted probability of cesarean delivery increases over time for all insurance categories, but the change over time differs depending on whether the birth is paid for by Medicaid or private insurance. In 2002, the probability that a 26-year-old woman with low risk would have a cesarean delivery differed by 1.9 percentage points based on whether she had Medicaid coverage or private insurance. By 2009, that difference had  increased to 4.1 percentage points.

Health insurance coverage affects hospital-based obstetric care. Changes over time in delivery mode and obstetric procedures differed depending on whether a pregnant woman had health insurance coverage for her delivery and depending on the payer (Medicaid vs private insurance). Controlling for  clinical, demographic, and hospital factors, uninsured women and women with Medicaid coverage received less intervention during childbirth (including  cesarean delivery, labor induction, and episiotomy) compared with privately insured women. These results are consistent with prior findings regarding the  relationship between insurance coverage and medical care, in general and as it specifically relates to maternity care.

 What our study adds is an  examination of differential time trends by payer and discovery of a more rapid rise in cesarean delivery rates among privately (versus publicly) insured births  over the past decade. With cesarean delivery being the most common inpatient surgery in US hospitals,

 this differential trend—although small in absolute  size&mdash;has an enormous magnitude in terms of potential payer costs and public health impacts.

When controlling for maternal and hospital factors, cesarean delivery rates increased more rapidly for privately versus publicly funded births, with important cost and health implications.

Trends in Hospital-Based Childbirth Care: The Role of Health Insurance

 The healthcare system in Israel faces difficulties similar to those of most industrialized countries, including limited resources, a growing chronically ill population, and demand for highquality care. Disease management programs (DMPs) for patients with a chronic illness aim to alleviate some of these problems, primarily by improving patient self-management skills and quality of care. This study surveyed the opinions of senior healthcare administrators regarding barriers, benefits, and support for implementing DMPs.

 A 21-item questionnaire was self-completed by 87 of 105 (83%) healthcare administrators included in the study. Participants were 65.5% male and 47% physicians, 25.3% nurses, 17.3% administrators, and 10.3% other healthcare professionals.

 The main perceived benefit of DMPs among all respondents was improving quality of care. Other benefits noted were better contact with patients  (81.6%) and better compliance with treatment (75.9%). Efficient long-term utilization of system resources was perceived as a benefit by only 58.6%. The main  perceived barriers to implementing DMPs were lack of budgetary resources (69%) and increased time required versus financial compensation received (63.2%).

 The benefits of DMPs were patient oriented; barriers were perceived as financial and limiting professional autonomy. Information regarding  long-term benefits (better patient outcomes) that ultimately provide better value for the system versus short-term barriers (increased costs and expenditures of  time without compensation) might encourage the implementation of DMPs in countries faced with a growing population of patients with at least 1 chronic illness.

A survey among healthcare executives regarding implementing disease management programs (DMPs) found that perceived benefits were patient oriented (improving quality of care, better contact with patients, and better compliance with treatment). Barriers were perceived as increased costs, expenditures of time without compensation, and limiting professional autonomy.

		Long-term advantages (better patient outcomes) need to be weighed against short-term difficulties (increased costs and expenditures of time without compensation) when implementing DMPs.

		Study results could be used as indicators to encourage the implementation of DMPs in countries faced with a growing population of patients with at least 1 chronic illness.

Healthcare markets are characterized by increasing costs, as well as by gaps in quality, safety, equity, and access. These are the result of market failure, observed when services are funded without evidence of cost-effectiveness. Chronic diseases are a major burden on the healthcare system. Disease management programs (DMPs) are the preferred means for helping chronically ill patients comply with their care. A DMP is defined by the World Health  Organization as “ongoing management of conditions over a period of years or decades, by providing and improving the necessary resources and support to enable patients’ self  management skills.”

Disease management programs aim to reduce waste, increase the efficiency of healthcare delivery, and reallocate resources to improve value.

 noted  that achieving high value for patients must become the overarching goal of healthcare delivery, with value defined as the health outcomes achieved per dollar  spent. If value improves, patients, payers, providers, and suppliers all can benefit, while the economic sustainability of the healthcare system is strengthened.

Disease management programs can lead to improvements in health. Interventions such as patient and provider education, feedback, and reminders have been  successful in increasing provider adherence to guidelines, enhancing patient satisfaction,

 and improving patient disease  control and health status

Disease management programs have also been effective for patients with asthma, arthritis, and coronary artery disease.

The economic effectiveness of DMPs is not clear.

 Some studies have found a net cost savings for DMPs and a return on investment of $1.26 per $1.00 spent on disease management services for patients with asthma, congestive heart failure, and diabetes.

Other studies showed that DMPs are associated with increased costs for diabetes and coronary artery disease,

 but not for asthma. Short-term costs might increase, but financial relief appears over the long term from a decrease in the incidence of diabetes-related complications and fewer hospital visits.

Financial savings are realized after about 3 years and depend on the type of intervention program.

 Some chronic obstructive pulmonary disease (COPD) programs have led to fewer hospitalizations and emergency department (ED) visits.

 However, a systematic review of multiple interventions in asthma and COPD revealed no significant improvements in the number of ED visits or in pulmonary function.

 demonstrated that by using a telephone-care management program, medical costs were reduced by almost 10% after 12 months. Other studies demonstrated that only DMPs that include financial incentives for physicians

 are efficient and lead to improved health outcomes and compliance.

Benefits from implementing DMPs largely depend on the structure of the specific healthcare system, including financial arrangements, staffing, and level of service. Although economic and organizational efficiency in a given system might improve, this does not necessarily imply that the improved efficiency will be replicated in other systems.

Israel’s national health insurance law provides all citizens with basic healthcare coverage. Healthcare is provided by 4 health funds, which are structured as  health maintenance organizations (HMOs). The HMOs are faced with growing costsof providing health services and increasing numbers of chronically ill  patients. They recently implemented DMPs for a number of chronic illnesses, including congestive heart failure, COPD, and depression. In the initial stages  of the programs, administrative difficulties were revealed, along with barriers to conducting these programs in primary care clinics. The focus of this study was  to investigate the origins of these obstacles. Therefore, we interviewed senior healthcare managers and policy makers in Israel to assess their attitudes  toward barriers to implementing DMPs within the national healthcare system.

A 21-item questionnaire was composed by the investigators, based on their experience in planning, implementing, and evaluating DMPs. Following a pretest of the questionnaire for clarity, in-depth interviews were conducted with 24 nurses and physicians in the health system who were familiar with  implementing DMPs. The questionnaire was revised based on their comments.

The questionnaire included 3 sections: (1) demographic and occupational  characteristics; (2) attitudes about the potential benefits of DMPs to the healthcare system, to community medical staff, and to patients with a chronic illness, and opinions about which professionals are most suited to managing a DMP; and (3) attitudes regarding barriers that might prevent healthcare system policy  makers and community medical staff from implementing DMPs. Responseswere ranked on a Likert scale from 1 (strongly agree) to 4 (strongly disagree). After each section, the respondent was asked to rank the answers marked “strongly agree” from 1 to 3, to determine a priority ranking for each series of questions (barriers, benefits, and professional management).

This cross-sectional survey was conducted in Israel from March to September 2010. The study population consisted of 105 senior healthcare administrators and included academic policy makers as well as top managers from the Ministry of Health and all 4 healthcare funds. Respondents’ professional backgrounds  included physicians, nurses, pharmacists, and social workers. The fields of mental health and dentistry were not included. All respondents had  held their current position for at least 2 years. Of these, 87 (83%) respondents agreed to schedule time to complete the survey in the presence of one of the investigators. This was done to improve the response rate. The interviews were conducted by investigators who were familiar with DMPs in Israel. They did  not provide any assistance in completing the questionnaires.

The data were analyzed using SAS version 9.2 (SAS Institute, Inc, Cary, North Carolina). For each statement in each question, 2 variables were built: 1 for  the Likert scale responses and 1 for ranking the statements that were marked “strongly agree.” Respondents were categorized into 3 groups: physicians, nurses, and others (paraprofessional and administrative personnel). For categorical variables, the Pearson 

 test or Fisher exact test, as appropriate, was used to compare the distributions of the 3 groups. The continuity-corrected 

A total of 87 senior executive managers, representing about 83% of all senior administrators of the national health care system, participated in the study. Most of the respondents (79.3%) held managerial positions in the HMOs, and 18 (20.7%) had positions in the Ministry of Health.

 presents the background characteristics of the study participants; 65.5% were male, 47% were physicians, 22 (25.3%) were nurses, and the remainder were paraprofessional and administrative professionals. Among the respondents, 63 (72.4%) had experience planning, implementing, or evaluating a DMP.

Attitudes Toward Disease Management Programs.

Almost all respondents (96.6%) replied that DMPs are important for the healthcare system and that healthcare organizations should include them in their 5-year strategic plans.

Overall, 79 (90.8%) respondents indicated that a DMP should be implemented by a multidisciplinary team.  Thirty-three (37.9%) stated that the program should be headed by a physician, 28 (32.2%) preferred a nurse, and only 6 (6.9%) indicated that a doctor and  nurse should head the program jointly. A significant link was found between the respondents’ professions and their views on who should head the DMP, with  58.5% of physicians saying it should be a physician, and 68.2% of the nurses stating that a nurse should head the program (

. A total of 82 (94.3%) participants responded that implementing DMPs was a very important component of the healthcare system. The majority (n = 44 [50.6%]) said that it was the responsibility of the HMOs to implement DMPs. The remaining responses were split between allocating the responsibility to the Ministry of Health (n = 21 [24.1%]) or to the Ministry of Health and the 4 national HMOs as a joint venture (n = 22 [25.3%]). In the latter case, the ministry would assume responsibility for administrative management and allocating resources to the programs, and the HMOs would implement and promote them.

Prioritizing Clinical Domains for Disease Management Programs. 

Diabetes and congestive heart failure were noted by 94.3% and 90.8% of the senior  managers, respectively, as conditions that could benefit from a DMP. Only 40.2% agreed that a DMP might be helpful for depression and anxiety. There were no differences between the opinions of senior physicians, nurses, paraprofessionals, and administrative personnel about the priority of implementing  these programs. However, more nurses than physicians thought that DMPs would be most effective in improving outcomes in illnesses such as hypertension (81.8% vs 56.1%, respectively;

 = .05), asthma (72.7% vs 46.3%, respectively; 

= .02), and COPD (90.9% vs 60% respectively,

Benefits to the Healthcare System From Implementing Disease Management Programs. 

 shows the perceived benefits of implementing a DMP. Improving quality of care was ranked as most the beneficial aspect by all respondents (89.6%). As seen in 

, nurses perceived more benefits from implementing DMP programs than physicians and other professional managers, including improving caregiver satisfaction, improving knowledge and professionalism, better contact with patients, and improving the patient’s quality of life.

Physicians and other managers expressed significantly stronger agreement than nurses with  the indicator, “Better access to health services and preventing errors.” On the other hand, both physicians and nurses agreed that the DMPs would contribute to efficient, long-term utilization of system resources.

Perceived barriers and benefits to implementing disease management programs among Israeli healthcare leaders could assist other  countries faced with increasing numbers of chronically ill patients.

Disease Management Programs: Barriers and Benefits

 To compare use of 7 shared electronic medical record (SMR) features by adult HIV patients.

 Observational cohort study of adult HIV-positive patients in the first 36 months following implementation of the SMR at Group Health and Kaiser Permanente Northern California.

Automated data from the 36 months following SMR implementation were assessed in 2 integrated delivery systems. Cox proportional hazards analysis identified factors associated with any SMR use.

 Most (3888/7398) patients used the SMR at least once. Users were most likely to view medical test results (49%), use secure messaging (43%), or request appointments (31%) or medication refills (30%). Initial use was associated with new prescription for antiretroviral therapy (rate ratio [RR] 1.65, 

 <.001), recent  change to a CD4+ count of fewer than 200 cells per microliter (RR = 1.34, 

 <.02), new HIV RNA of 75 or more copies per milliliter (RR = 1.63, 

 <.001), or  recent increase in non-HIV comorbidity score (RR = 1.49,

 = .0001). Users were less likely to be women (RR = 0.49, 

= .0001), injection drug users (RR = 0.59,  

 = .0001), or from lower—socioeconomic status neighborhoods (RR = 0.68, P = .0001), and were less likely to be black (RR = 0.38, 

 = .0001) or Asian/Pacific Islander (RR = 0.59, 

 SMR use was higher among HIVpatients who had indicators of recent increases in healthcare needs and lower among several vulnerable populations.

This observational cohort study compared use of 7 features of an online shared medical record by adult patients with HIV.

Use was higher among those with HIV who had indicators of recent increases in healthcare needs and lower among several vulnerable populations.

Healthcare providers and systems should support use of online shared medical records among patients with HIV as part of broader efforts to improve overall access to care.

Ongoing collaboration with providers is essential for care of patients with HIV. To reduce HIV-related morbidity and mortality, patients and providers monitor CD4+ T-cell counts and HIV viral loads, and initiate and adjust antiretroviral therapy. Patients on antiretroviral therapy must adhere tightly to the regimen for benefits, while managing the medications’ frequent side effects.1 Healthcare systems that enable good communication with providers and access to services such as laboratory monitoring and medication refills are critical for patients to manage HIV infection successfully.

Patient websites providing secure access to electronic medical records that are shared between patients and healthcare providers may help meet the ongoing care needs of many patients with HIV. Also known as integrated personal health records, these web-based shared electronic medical records (SMRs) can provide a constellation of services for patients, typically including exchanging secure electronic messages and scheduling appointments with healthcare providers,  ordering medication refills, and viewing care plans, medical test results, and other portions of the electronic medical record.

 Proposed federal meaningful  use criteria for electronic health records support patients’ use of the SMR, including secure messaging with providers.

 Many of these services may help patients with HIV, particularly during times of heightened need (eg, when starting new antiretroviral medications or when there is a significant CD4+ count decrease).

Despite the SMR’s potential, some groups of patients disproportionately affected by HIV may be less likely to use it. HIV is estimated to be 9 times more common in blacks and nearly 3 times more common in Hispanics

 than in whites; black and Hispanic populations are also less likely to receive highly active antiretroviral  therapy7 and experimental treatments. Individuals with low socioeconomic status (SES) are twice as likely to have HIV

and  less likely to receive highly active antiretroviral therapy. Older patients with HIV have faster progression of disease, with treatment often complicated by coexisting chronic health conditions.

All these sociodemographic groups are also less likely to use the Internet

 An initial study of  personal health record use among patients with HIV receiving care at San Francisco General Hospital also found that users were more likely to be Caucasian and non-Hispanic.

 Further understanding of potential differences in SMR use by patients with HIV who belong to vulnerable populations is essential to ensure that healthcare is designed to meet the needs of all patients with HIV. These potential differences are particularly important if the SMR is being used to support  care at critical times, such as initiation of antiretroviral medications or a drop in CD4+ cell count.

We performed a cohort study of adult HIV-positive patients in the first 36 months following implementation of the SMR at Group Health (GH) (August 1, 2003, to July 31, 2006) and Kaiser Permanente Northern California (KPNC) (November 1, 2005, to October 31, 2008). Group Health and KPNC are large,  integrated healthcare delivery organizations providing multidisciplinary care, including HIV specialty care. The study population included enrollees 18 years  or older in either institution’s HIV registry. Patients were followed from the date they met eligibility criteria (

18 years of age, HIV positive, enrolled in health plan) until the earliest of disenrollment, death, or the end of the study period.

Beginning in 2003 at GH and 2005 at KPNC, all patients could access an SMR (www.ghc.org or www.kp.org) with 7 features common to both sites: secure messaging with healthcare providers; requesting medication refills; requesting inperson appointments; and viewing after-visit summaries, allergies,  immunizations, and test results (excluding CD4+ and HIV RNA results at KPNC). Detailed descriptions of the patient websites at GH

 were  previously reported. Patients verified their identity to GH or KPNC before using these features.

 We hypothesized that SMR use would be higher among  those with a recent heightened need for care but lower among racial and ethnic minorities, older patients, and those from lower-SES groups.

The KPNC HIV registry18,19 includes all known cases since the early 1980s; the GH registry, since 1997. Registry data include sex; birth date; race/ethnicity; dates of known HIV infection and AIDS diagnoses; and at KPNC only, HIV transmission risk factors. There are also historical databases at KPNC and GH on  member demographics, prescriptions, hospitalizations, outpatient visits, and laboratory tests, including CD4+ T-cell count and HIV RNA test results, health insurance status, and zip code. Date of death was identified from hospitalizations, membership files, California and Washington state death certificates,

and Social Security Administration data sets.

 The primary outcome of interest was any SMR use defined as using at least 1 of the 7 SMR features during the study period. Secondary outcome was continued SMR use (mean days of SMR use per month). Rates of use were measured as the number of days per month in which patients used any of the SMR features.

Variables Potentially Associated With Shared Medical Record Use. 

Primary predictors were recent increase in healthcare need, race/ethnicity, neighborhood SES, and age. We defined recent increase in healthcare need as 1 of the following clinical events occurring within the prior 3 months: start or restart of antiretroviral therapy; new CD4+ count of fewer than 200 cells per microliter; newly quantifiable HIV RNA of 75 or more copies per milliliter; or worsening comorbidity unrelated to HIV. Non-HIV morbidity was measured using a modified Charlson Comorbidity Index, excluding HIV/AIDS diagnoses.

 Neighborhood SES was categorized as low for a patient if at least 20% of 2000 Census block residents had an income below $20,000 or at least 25% of   residents over age 25 years had not completed high school.

Secondary predictors included sex, HIV risk factors, insurance status, time with health  plan, and specific comorbid conditions (depression and hepatitis B and C). Predictor selection was based on prior studies of SMR use in other  populations

 and prior studies of access to care in people with HIV.

 Depression was defined by outpatient diagnosis in prior 12 months. HIV  transmission risk factors and history of hepatitis B and C were from the HIV and the hepatitis C virus/hepatitis B virus registries at each site.

We used Cox proportional hazards analysis to identify the factors associated with any use of the SMR. Outcome was time to first use; rate ratios (RRs; hazard ratios) compared the rate of initial use (percentage of patients per month who first used SMR) with that of a reference group. Separate Cox models were fit to each variable, first adjusting for site only, and then for site, sex, age, and non—HIV-related morbidity.

Race/ethnicity analyses adjusted for age, sex, and a modified Charlson Comorbidity Index (without HIV/AIDS)

Use of online shared records was higher among HIV patients who had indicators of recent increases in healthcare needs and lower among several vulnerable populations.

April 2013

Primary Nonadherence to Statin Therapy: Patients' Perceptions

Trends in Hospital-Based Childbirth Care: The Role of Health Insurance

Disease Management Programs: Barriers and Benefits

Use of Web-Based Shared Medical Records Among Patients With HIV

Retail Clinic Utilization Associated With Lower Total Cost of Care

Health Plan Innovations in Delivery System Reforms

More Comprehensive Discussion of CRC Screening Associated With Higher Screening

Prescription Opioid Abuse: Challenges and Opportunities for Payers

Comparative Effectiveness of Early Natalizumab Treatment in JC Virus-Negative Relapsing-Remitting Multiple Sclerosis

Effects of Coverage Gap Reform on Adherence to Diabetes Medications