ABSTRACT
BACKGROUND AND OBJECTIVES: The coronavirus disease-2019 (COVID-19) pandemic is transforming the health care sector. As health care organizations move from crisis mobilization to a new landscape of health and social needs, organizational health literacy offers practical building blocks to provide high-quality, efficient, and meaningful care to patients and their families. Organizational health literacy is defined by the Institute of Medicine as "the degree to which an organization implements policies, practices, and systems that make it easier for people to navigate, understand, and use information and services to take care of their health." METHODS: This article synthesizes insights from organizational health literacy in the context of current major health care challenges and toward the goal of innovation in patient-centered care. We first provide a brief overview of the origins and outlines of organizational health literacy research and practice. Second, using an established patient-centered innovation framework, we show how the existing work on organizational health literacy can offer a menu of effective, patient-centered innovative options for care delivery systems to improve systems and outcomes. Finally, we consider the high value of management focusing on organizational health literacy efforts, specifically for patients in health care transitions and in the rapid transformation of care into myriad distance modalities. RESULTS: This article provides practical guidance for systems and informs decisions around resource allocation and organizational priorities to best meet the needs of patient populations even in the face of financial and workforce disruption. CONCLUSIONS: Organizational health literacy principles and guidelines provide a road map for promoting patient-centered care even in this time of crisis, change, and transformation. Health system leaders seeking innovative approaches can have access to well-established tool kits, guiding models, and materials toward many organizational health literacy goals across treatment, diagnosis, prevention, education, research, and outreach.
Subject(s)
COVID-19/epidemiology , Health Literacy , Patient-Centered Care , Health Literacy/methods , Health Literacy/organization & administration , Health Priorities/organization & administration , Humans , Leadership , Patient-Centered Care/methods , Patient-Centered Care/organization & administration , Quality Improvement/organization & administration , Quality of Health Care/organization & administration , Resource Allocation/methods , Resource Allocation/organization & administrationABSTRACT
Surveillance of chronic hepatitis C virus (HCV) cases faces limitations that result in delays and under-reporting. With increasing use of electronic health records (EHRs), the authors evaluated the predictive value of using International Classification of Diseases, Ninth Revision (ICD-9) codes to identify chronic HCV cases from EHR data. Longitudinal EHR data from 4 health care systems during 2006-2012 were evaluated. Using chart abstraction and review to confirm chronic HCV cases ("gold standard" definition), the authors calculated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 2 case definitions: (1) ≥2 ICD-9 codes separated by ≥6 months and (2) ≥1 positive HCV RNA (ribonucleic acid) test. Among 2,718,995 patients, 20,779 (0.8%) with ICD-9 codes indicating a likely diagnosis of chronic HCV infection were identified; 13,595 (65.4%) of these were randomly selected for review. Case definition 1 (≥2 ICD-9 codes separated by ≥6 months) had 70.3% sensitivity, 91.9% PPV, 99.9% specificity, and 99.9% NPV while case definition 2 (≥1 positive HCV RNA test) had 74.1% sensitivity, 97.4% PPV, 99.9% specificity, and 99.9% NPV. The predictive values of these alternate EHR-derived ICD-9 code-based case definitions suggest that these measures may be useful in capturing the burden of diagnosed chronic HCV infections. Their use can augment current chronic HCV case surveillance efforts; however, their accuracy may vary by length of observation and completeness of EHR data.
ABSTRACT
BACKGROUND: Research suggests depression and alcohol misuse are highly prevalent among chronic hepatitis C (CHC) patients, which is of clinical concern. AIMS: To compare ICD-9 codes for depression and alcohol misuse to validated survey instruments. METHODS: Among CHC patients, we assessed how well electronic ICD-9 codes for depression and alcohol misuse predicted these disorders using validated instruments. RESULTS: Of 4874 patients surveyed, 56% were male and 52% had a history of injection drug use. Based on the PHQ-8, the prevalence of depression was 30% compared to 14% based on ICD-9 codes within 12 months of survey, 37% from ICD-9 codes any time before or within 12 months after survey, and 48% from ICD-9 codes any time before or within 24 months after survey. ICD-9 codes predicting PHQ-8 depression had a sensitivity ranging from 59 to 88% and a specificity ranging from 33 to 65%. Based on the AUDIT-C, the prevalence of alcohol misuse was 21% compared to 3-23% using ICD-9 codes. The sensitivity of ICD-9 codes to predict AUDIT-C score ranged from 9 to 35% and specificity from 80 to 98%. Overall 39% of patients reported ever binge drinking, with a sensitivity of ICD-9 to predict binge drinking ranging from 7 to 33% and a specificity from 84 to 98%. More than half of patients had either an ICD-9 code for depression, a survey score indicating depression, or both (59%); more than one-third had the same patterns for alcohol misuse (36%). CONCLUSIONS: ICD-9 codes were limited in predicting current depression and alcohol misuse, suggesting that caution should be exercised when using ICD-9 codes to assess depression or alcohol misuse among CHC patients.
Subject(s)
Alcoholism/classification , Alcoholism/epidemiology , Data Mining/methods , Depression/classification , Depression/epidemiology , Hepatitis C, Chronic/classification , Hepatitis C, Chronic/epidemiology , International Classification of Diseases , Adolescent , Adult , Aged , Alcoholism/diagnosis , Depression/diagnosis , Electronic Health Records , Female , Health Surveys , Hepatitis C, Chronic/diagnosis , Humans , Male , Middle Aged , Prevalence , Time Factors , United States/epidemiology , Young AdultABSTRACT
OBJECTIVE: To compare bariatric surgery outcomes according to preoperative mental illness category. METHODS: Electronic health record data from several US healthcare systems were used to compare outcomes of four groups of patients who underwent bariatric surgery in 2012 and 2013. These included the following: people with (1) no mental illness, (2) mild-to-moderate depression or anxiety, (3) severe depression or anxiety, and (4) bipolar, psychosis, or schizophrenia spectrum disorders. Groups were compared on weight loss trajectory using generalized estimating equations using B-spline bases and on all-cause emergency department visits and hospital days using zero-inflated Poisson and negative binomial regression up to 2 years after surgery. Models were adjusted for demographic and health covariates, including baseline healthcare use. RESULTS: Among 8,192 patients, mean age was 44.3 (10.7) years, 79.9% were female, and 45.6% were white. Fifty-seven percent had preoperative mental illness. There were no differences between groups for weight loss, but patients with preoperative severe depression or anxiety or bipolar, psychosis, or schizophrenia spectrum disorders had higher follow-up levels of emergency department visits and hospital days compared to those with no mental illness. CONCLUSIONS: In this multicenter study, mental illness was not associated with differential weight loss after bariatric surgery, but additional research could focus on reducing acute care use among these patients.
Subject(s)
Bariatric Surgery/methods , Depressive Disorder, Major/complications , Mental Health/trends , Adult , Cohort Studies , Electronic Health Records , Female , Humans , MaleABSTRACT
OBJECTIVE: The objective of this study was to characterize racial-ethnic variation in diagnoses and treatment of mental disorders in large not-for-profit health care systems. METHODS: Participating systems were 11 private, not-for-profit health care organizations constituting the Mental Health Research Network, with a combined 7,523,956 patients age 18 or older who received care during 2011. Rates of diagnoses, prescription of psychotropic medications, and total formal psychotherapy sessions received were obtained from insurance claims and electronic medical record databases across all health care settings. RESULTS: Of the 7.5 million patients in the study, 1.2 million (15.6%) received a psychiatric diagnosis in 2011. This varied significantly by race-ethnicity, with Native American/Alaskan Native patients having the highest rates of any diagnosis (20.6%) and Asians having the lowest rates (7.5%). Among patients with a psychiatric diagnosis, 73% (N=850,585) received a psychotropic medication. Non-Hispanic white patients were significantly more likely (77.8%) than other racial-ethnic groups (odds ratio [OR] range .48-.81) to receive medication. In contrast, only 34% of patients with a psychiatric diagnosis (N=548,837) received formal psychotherapy. Racial-ethnic differences were most pronounced for depression and schizophrenia; compared with whites, non-Hispanic blacks were more likely to receive formal psychotherapy for their depression (OR=1.20) or for their schizophrenia (OR=2.64). CONCLUSIONS: There were significant racial-ethnic differences in diagnosis and treatment of psychiatric conditions across 11 U.S. health care systems. Further study is needed to understand underlying causes of these observed differences and whether processes and outcomes of care are equitable across these diverse patient populations.
Subject(s)
Mental Disorders/ethnology , Mental Disorders/therapy , Mental Health Services/statistics & numerical data , Psychotherapy/statistics & numerical data , Psychotropic Drugs/therapeutic use , Adolescent , Adult , Aged , Female , Humans , Male , Mental Disorders/drug therapy , Middle Aged , United States/ethnology , Young AdultABSTRACT
OBJECTIVES: To examine the relationship between patient characteristics and medication adherence trajectories for patients with congestive heart failure (CHF). STUDY DESIGN: Historical prospective study. METHODS: We conducted a secondary analysis of data assembled for the Practice Variation and Care Outcomes (PRAVCO) study, which examined patterns of cardiovascular care. We used group based trajectory modeling to define medication adherence trajectories, and then modeled factors associated with belonging to a trajectory group during the 6year period from 2005 to 2010 (n = 10,986). We focused on the use of angiotensin-converting enzyme (ACE) inhibitors or angiotensin II receptor blockers (ARBs) for secondary prevention of CHF. RESULTS: Four trajectory groups were optimal in characterizing adherence level patterns: 1) low adherence group, with an initial average adherence rate of 62% that dropped to between 40% and 50%; 2) increasing adherence group, with an initial average adherence rate of 55% that increased to 90%; 3) decreasing adherence group, with an initial average adherence rate above 90% that decreased to 60%; 4) high adherence group, with an average adherence rate consistently above 90%. Age, region, education, smoking, and race were all significantly associated with the likelihood of belonging to a particular trajectory. Nonwhites were less likely to be in the high adherence group, and smoking was more common in the low adherence group (22%) than in the high group (10%); increasing body mass index and Charlson Comorbidity Index (CCI) scores were also associated with being in the low adherence group. CONCLUSIONS: Population characteristics associated with sustained low adherence might be used to target interventions and improve vulnerable patients' prospects of heart health.
Subject(s)
Heart Failure/drug therapy , Medication Adherence , Age Factors , Aged , Angiotensin Receptor Antagonists/therapeutic use , Angiotensin-Converting Enzyme Inhibitors/therapeutic use , Educational Status , Female , Heart Failure/epidemiology , Humans , Male , Middle Aged , Pacific States/epidemiology , Prospective Studies , Racial Groups/statistics & numerical data , Smoking/epidemiologyABSTRACT
OBJECTIVE: The goal of this study was to characterize racial-ethnic differences in mental health care utilization associated with postpartum depression in a multiethnic cohort of Medicaid recipients. METHODS: In a retrospective cohort study, administrative claims data from New Jersey's Medicaid program were obtained for 29,601 women (13,001 whites, 13,416 blacks, and 3,184 Latinas) who delivered babies between July 2004 and October 2007. Racial-ethnic differences were estimated with logistic regression for initiation of antidepressant medication or outpatient mental health visits within six months of delivery, follow-up (a prescription refill or second visit), and continued mental health care (at least three visits or three filled antidepressant prescriptions within 120 days). RESULTS: Nine percent (N=1,120) of white women initiated postpartum mental health care, compared with 4% (N=568) of black women and 5% (N=162) of Latinas. With analyses controlling for clinical factors, the odds of initiating treatment after delivery were significantly (p<.001) lower for blacks (adjusted odds ratio [AOR]=.43) and Latinas (AOR=.59) compared with whites. Among those who initiated treatment, blacks and Latinas were less likely than whites to receive follow-up treatment (blacks, AOR=.66, p<.001; Latinas, AOR=.67, p<.05) or continued care (blacks, AOR=.81, p=.069; Latinas, AOR=.67, p<.05). Among those who initiated antidepressant treatment, black women and Latinas were less likely than whites to refill a prescription. CONCLUSIONS: There were significant racial-ethnic differences in depression-related mental health care after delivery. Suboptimal treatment was prevalent among all low-income women in the study. However, racial and ethnic disparities in the initiation and continuation of postpartum depression care were particularly troubling and warrant clinical and policy attention.
Subject(s)
Antidepressive Agents/therapeutic use , Black People/psychology , Black People/statistics & numerical data , Community Mental Health Services/statistics & numerical data , Depression, Postpartum/ethnology , Healthcare Disparities/statistics & numerical data , Hispanic or Latino/psychology , Hispanic or Latino/statistics & numerical data , White People/psychology , White People/statistics & numerical data , Adolescent , Adult , Aftercare/psychology , Aftercare/statistics & numerical data , Cohort Studies , Depression, Postpartum/epidemiology , Drug Utilization/statistics & numerical data , Female , Humans , Medicaid/statistics & numerical data , Medication Adherence/ethnology , Medication Adherence/psychology , Medication Adherence/statistics & numerical data , New Jersey , Odds Ratio , Probability , Regression Analysis , Retrospective Studies , United States , Utilization Review/statistics & numerical data , Young AdultABSTRACT
OBJECTIVE: The study's objective was to assess the effects of automated telephone outreach with speech recognition (ATO-SR) on diabetes-related testing. RESEARCH DESIGN AND METHODS: We identified 1,200 health plan members who were overdue for diabetes-related testing and randomly allocated 600 to ATO-SR and 600 to usual care (no intervention). The intervention included three interactive calls encouraging recommended testing. The primary outcome was retinopathy testing, since this was the health plan's principal goal. Tests for glycemia, hyperlipidemia, and nephropathy were secondary outcomes. RESULTS: In total, 232 participants (39%) verbally responded to the calls. There was no difference between the intervention and the usual care groups in the primary outcome (adjusted hazard ratio 0.93 [95% CI 0.71-1.22]) and no effect of the intervention on any of the secondary outcomes. CONCLUSIONS: Fewer than 40% of the patients randomized to ATO-SR interacted verbally with the system. The intervention had no effect on the study's outcomes.
Subject(s)
Community-Institutional Relations , Diabetes Mellitus, Type 2/diagnosis , Diabetes Mellitus, Type 2/therapy , Speech Recognition Software , Telephone , Diabetic Nephropathies/diagnosis , Diabetic Nephropathies/therapy , Diabetic Retinopathy/diagnosis , Diabetic Retinopathy/therapy , Female , Humans , Hyperglycemia/diagnosis , Hyperglycemia/therapy , Hyperlipidemias/diagnosis , Hyperlipidemias/therapy , Insurance, Health , Kaplan-Meier Estimate , Male , Middle Aged , Organizations, Nonprofit , Patient Participation , Proportional Hazards ModelsABSTRACT
OBJECTIVE: Many patients do not receive guideline-recommended care for diabetes and other chronic conditions. Automated speech-recognition telephone outreach to supplement in-person physician-patient communication may enhance patient care for chronic illness. We conducted this study to inform the development of an automated telephone outreach intervention for improving diabetes care among members of a large, not-for-profit health plan. DESIGN: In-depth telephone interviews with qualitative analysis. SETTING: participants Individuals with diabetes (n=36) enrolled in a large regional health plan in the USA. Main outcome measure Patients' opinions about automated speech-recognition telephone technology. RESULTS: Patients who were recently diagnosed with diabetes and some with diabetes for a decade or more expressed basic informational needs. While most would prefer to speak with a live person rather than a computer-recorded voice, many felt that the automated system could successfully supplement the information they receive from their physicians and could serve as an integral part of their care. Patients suggested that such a system could provide specific dietary advice, information about diabetes and its self-care, a call-in menu of information topics, reminders about laboratory test results and appointments, tracking of personal laboratory results and feedback about their self-monitoring. CONCLUSIONS: While some patients expressed negative attitudes toward automated speech recognition telephone systems generally, most felt that a variety of functions of such a system could be beneficial to their diabetes care. In-depth interviews resulted in substantive input from health plan members for the design of an automated telephone outreach system to supplement in-person physician-patient communication in this population.
Subject(s)
Diabetes Mellitus/therapy , Patient Education as Topic/methods , Remote Consultation/methods , Telephone , User-Computer Interface , Adult , Aged , Automation , Female , Humans , Male , Middle Aged , Patient Satisfaction , Self Care/methods , Speech , Young AdultABSTRACT
OBJECTIVE: The purpose of this study was to examine medication adherence and other self-management practices as potential determinants of higher glycemic risk among black relative to white patients. RESEARCH DESIGN AND METHODS: We used a retrospective, longitudinal repeated-measures design to model the contribution of medication adherence to black-white differences in A1C among type 2 diabetic patients at a large multispecialty group practice. We identified 1,806 adult (aged >/=18 at diagnosis) patients (467 black and 1,339 white) with newly initiated oral hypoglycemic therapy between 1 December 1994 and 31 December 2000. Race was identified using an electronic medical record and patient self-report. Baseline was defined as the 13 months preceding and included the month of therapy initiation. All patients were required to have at least 12 months of follow-up. RESULTS: At initiation of therapy, black patients had higher average A1C values compared with whites (9.8 vs. 8.9, a difference of 0.88; P < 0.0001). Blacks had lower average medication adherence during the first year of therapy (72 vs. 78%; P < 0.0001). Although more frequent medication refills were associated with lower average A1C values, adjustment for adherence did not eliminate the black-white gap. CONCLUSIONS: We found persistent racial differences in A1C that were not explained by differences in medication adherence. Our findings suggest that targeting medication adherence alone is unlikely to reduce disparities in glycemic control in this setting. Further research is needed to explore possible genetic and environmental determinants of higher A1C among blacks at diagnosis, which may represent a critical period for more intensive intervention.
Subject(s)
Diabetes Mellitus, Type 2/blood , Glycated Hemoglobin/metabolism , Patient Compliance , Racial Groups/statistics & numerical data , Administration, Oral , Adult , Aged , Black People/statistics & numerical data , Body Weight , Diabetes Mellitus, Type 2/drug therapy , Diabetes Mellitus, Type 2/psychology , Female , Humans , Hypoglycemic Agents/administration & dosage , Hypoglycemic Agents/therapeutic use , Longitudinal Studies , Male , Middle Aged , Retrospective Studies , White People/statistics & numerical dataABSTRACT
BACKGROUND: One approach to improving outcomes for minority diabetics may be through better self-care. However, minority patients may encounter barriers to better self-care even within settings where variations in quality of care and insurance are minimized. OBJECTIVE: The objective of the study was to evaluate racial differences in long-term glucose self-monitoring and adherence rates in an HMO using evidence-based guidelines for self-monitoring. DESIGN: Retrospective cohort study using 10 years (1/1/1993-12/31/2002) of electronic medical record data was used. PATIENTS: Patients were 1,732 insured adult diabetics of black or white race newly initiated on hypoglycemic therapy in a large multi-specialty care group practice. MEASUREMENTS: Outcomes include incidence and prevalence of glucose self-monitoring, intensity of use, and rate of adherence to national recommended standards. RESULTS: We found no evidence of racial differences in adjusted initiation rates of glucose self-monitoring among insulin-treated patients, but found lower rates of initiation among black patients living in low-income areas. Intensity of glucose self-monitoring remained lower among blacks than whites throughout follow-up [IRR for insulin = 0.41 (0.27-0.62); IRR for oral hypoglycemic = 0.75 (0.63, 0.90)], with both groups monitoring well below recommended standards. Among insulin-treated patients, <1% of blacks and <10% of whites were self-monitoring 3 times per day; 36% of whites and 10% of blacks were self-monitoring at least once per day. CONCLUSIONS: Adherence to glucose self-monitoring standards was low, particularly among blacks, and racial differences in self-monitoring persisted within a health system providing equal access to services for diabetes patients. Early and continued emphasis on adherence among black diabetics may be necessary to reduce racial differences in long-term glucose self-monitoring.
Subject(s)
Black or African American/statistics & numerical data , Blood Glucose Self-Monitoring/statistics & numerical data , Diabetes Mellitus, Type 2/ethnology , Diabetes Mellitus, Type 2/therapy , Health Maintenance Organizations , Patient Compliance/ethnology , White People/statistics & numerical data , Adult , Aged , Diabetes Mellitus, Type 2/drug therapy , Female , Humans , Hypoglycemic Agents/therapeutic use , Insulin/therapeutic use , Male , Massachusetts , Middle Aged , Multivariate AnalysisABSTRACT
OBJECTIVE: Clinical inertia has been identified as a critical barrier to glycemic control in type 2 diabetes. We assessed the relationship between patients' initial medication adherence and subsequent regimen intensification among patients with persistently elevated A1C levels. RESEARCH DESIGN AND METHODS: We analyzed an inception cohort of 2,065 insured patients with type 2 diabetes who were newly started on hypoglycemic therapy and were followed for at least 3 years between 1992 and 2001. Medication adherence was assessed by taking the ratio of medication days dispensed (from pharmacy records) to medication days prescribed (as documented in the medical record) for the first prescribed hypoglycemic drug. Adherence was measured for the period between medication initiation and the next elevated A1C result measured at least 3 months later; intensification was defined as a dose increase or the addition of a second hypoglycemic agent. RESULTS: Patients were aged (mean +/- SD) 55.4 +/- 12.2 years; 53% were men, and 19% were black. Baseline medication adherence was 79.8 +/- 19.3%. Patients in the lowest quartile of adherence were significantly less likely to have their regimens increased within 12 months of their first elevated A1C compared with patients in the highest quartile (27 vs. 37%, respectively, with increased regimens if A1C is elevated, P < 0.001). In multivariate models adjusting for patient demographic and treatment factors, patients in the highest adherence quartile had 53% greater odds of medication intensification after an elevated A1C (95% CI 1.11-1.93, P = 0.01). CONCLUSIONS: Among insured diabetic patients with elevated A1C, level of medication adherence predicted subsequent medication intensification. Poor patient self-management behavior increases therapeutic clinical inertia.