Patients' Perspectives on Plans Generated During Primary Care Visits and Self-Reported Adherence at 3 Months: Data From a Randomized Trial.

BACKGROUND: Effective primary care necessitates follow-up actions by the patient beyond the visit. Prior research suggests room for improvement in patient adherence. OBJECTIVE: This study sought to understand patients' views on their primary care visits, the plans generated therein, and their self-reported adherence after 3 months. METHODS: As part of a large multisite cluster randomized pragmatic trial in 3 health care organizations, patients completed 2 surveys-the first within 7 days after the index primary care visit and another 3 months later. For this analysis of secondary outcomes, we combined the results across all study participants to understand patient adherence to care plans. We recorded patient characteristics and survey responses. Cross-tabulation and chi-square statistics were used to examine bivariate associations, adjusting for multiple comparisons when appropriate. We used multivariable logistic regression to assess how patients' intention to follow, agreement, and understanding of their plans impacted their plan adherence, allowing for differences in individual characteristics. Qualitative content analysis was conducted to characterize the patient's self-reported plans and reasons for adhering (or not) to the plan 3 months later. RESULTS: Of 2555 patients, most selected the top box option (9=definitely agree) that they felt they had a clear plan (n=2011, 78%), agreed with the plan (n=2049, 80%), and intended to follow the plan (n=2108, 83%) discussed with their provider at the primary care visit. The most common elements of the plans reported included reference to exercise (n=359, 14.1%), testing (laboratory, imaging, etc; n=328, 12.8%), diet (n=296, 11.6%), and initiation or adjustment of medications; (n=284, 11.1%). Patients who strongly agreed that they had a clear plan, agreed with the plan, and intended to follow the plan were all more likely to report plan completion 3 months later (P<.001) than those providing less positive ratings. Patients who reported plans related to following up with the primary care provider (P=.008) to initiate or adjust medications (P≤.001) and to have a specialist visit were more likely to report that they had completely followed the plan (P=.003). Adjusting for demographic variables, patients who indicated intent to follow their plan were more likely to follow-through 3 months later (P<.001). Patients' reasons for completely following the plan were mainly that the plan was clear (n=1114, 69.5%), consistent with what mattered (n=1060, 66.1%), and they were determined to carry through with the plan (n=887, 53.3%). The most common reasons for not following the plan were lack of time (n=217, 22.8%), having decided to try a different approach (n=105, 11%), and the COVID-19 pandemic impacted the plan (n=105, 11%). CONCLUSIONS: Patients' initial assessment of their plan as clear, their agreement with the plan, and their initial willingness to follow the plan were all strongly related to their self-reported completion of the plan 3 months later. Patients whose plans involved lifestyle changes were less likely to report that they had "completely" followed their plan. TRIAL REGISTRATION: ClinicalTrials.gov NCT03385512; https://clinicaltrials.gov/study/NCT03385512. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/30431.

Developing a PRogram to Educate and Sensitize Caregivers to Reduce the Inappropriate Prescription Burden in the Elderly with Alzheimer's Disease (D-PRESCRIBE-AD): Trial protocol and rationale of an open-label pragmatic, prospective randomized controlled trial.

CONTEXT: Potentially inappropriate prescribing of medications in older adults, particular those with dementia, can lead to adverse drug events including falls and fractures, worsening cognitive impairment, emergency department visits, and hospitalizations. Educational mailings from health plans to patients and their providers to encourage deprescribing conversations may represent an effective, low-cost, "light touch", approach to reducing the burden of potentially inappropriate prescription use in older adults with dementia. OBJECTIVES: The objective of the Developing a PRogram to Educate and Sensitize Caregivers to Reduce the Inappropriate Prescription Burden in Elderly with Alzheimer's Disease (D-PRESCRIBE-AD) trial is to evaluate the effect of a health plan based multi-faceted educational outreach intervention to community dwelling patients with dementia who are currently prescribed sedative/hypnotics, antipsychotics, or strong anticholinergics. METHODS: The D-PRESCRIBE-AD is an open-label pragmatic, prospective randomized controlled trial (RCT) comparing three arms: 1) educational mailing to both the health plan patient and their prescribing physician (patient plus physician arm, n = 4814); 2) educational mailing to prescribing physician only (physician only arm, n = 4814); and 3) usual care (n = 4814) among patients with dementia enrolled in two large United States based health plans. The primary outcome is the absence of any dispensing of the targeted potentially inappropriate prescription during the 6-month study observation period after a 3-month black out period following the mailing. Secondary outcomes include dose-reduction, polypharmacy, healthcare utilization, mortality and therapeutic switching within targeted drug classes. CONCLUSION: This large pragmatic RCT will contribute to the evidence base on promoting deprescribing of potentially inappropriate medications among older adults with dementia. If successful, such light touch, inexpensive and highly scalable interventions have the potential to reduce the burden of potentially inappropriate prescribing for patients with dementia. ClinicalTrials.gov Identifier: NCT05147428.

Motivating deprescribing conversations for patients with Alzheimer's disease and related dementias: a descriptive study.

Introduction: Older adults with Alzheimer's disease and related dementias (ADRD) are at increased risk of harm due to prescribing of potentially inappropriate medications. Encouraging patients and caregivers to talk with their providers about potentially inappropriate medications could stimulate deprescribing. Our objective was to explore whether mailing educational materials to patients with ADRD might activate patients or caregivers to initiate a conversation with their provider about potentially inappropriate medications. Methods: We conducted semi-structured interviews with patients with ADRD, caregivers of patients with ADRD, and healthcare providers. All participants were shown educational materials referencing potentially inappropriate medications and suggestions to promote deprescribing. Interviews explored reactions to the materials, the idea of patients and caregivers initiating a conversation about deprescribing, and the deprescribing process. Interview transcripts were analyzed using inductive thematic analysis. Results: We conducted a total of 27 interviews: 9 with caregivers only, 2 with patients only, 3 with patient-caregiver dyads, and 13 with providers. Patients and caregivers reported that if a medication might cause harm, it would motivate them to talk to their provider about the medication. Trust in the provider could facilitate or inhibit such conversations; conversations would be more likely if there were prior positive experiences asking questions of the provider. Providers were receptive to patients and caregivers initiating conversations about their medications, as they valued deprescribing as part of their clinical practice and welcome informed patients and caregivers as participants in decision-making about medication. Conclusion: Mailing educational materials about potentially inappropriate medications to community-dwelling patients with ADRD may promote deprescribing conversations. Ongoing pragmatic trials will determine whether such interventions stimulate deprescribing conversations and achieve reductions in prescribing of inappropriate medications. Plain Language Summary: Encouraging patients with Alzheimer's disease to talk with their providers about medications that may cause harm Introduction: Older adults with Alzheimer's disease and related dementias (ADRD) are sometimes prescribed medications that may cause harm, especially when taken for extended periods of time. Patients and their caregivers may not know about the risks. Doctors know of the risks but may not address them due to competing priorities or other challenges in providing care to these patients with complex needs. Encouraging the patient or their caregiver to talk to their doctor about their medications might help to reduce the use of medications that are not beneficial. This study's goal was to explore whether sending educational materials to patients with ADRD might encourage patients or caregivers to ask their doctor about their medications.Methods: We interviewed patients with ADRD, caregivers, and doctors. We showed them educational materials that suggested patients and their caregivers talk to their doctor about reducing or stopping medications that may be harmful. We asked for reactions to the materials and to the idea of talking to the doctor about stopping the medication.Results: We conducted 27 interviews: 9 with caregivers only, 2 with patients only, 3 with patient-caregiver dyads, and 12 with doctors. Patients and caregivers said learning that a medication might cause harm would motivate them to talk to their doctor about the medication. Trust in their doctor was important. Some patients and caregivers were comfortable asking questions about medications, while others were reluctant to challenge the doctor. Doctors were open to patients and caregivers asking about medications and felt it was important that patients not take medications that are not needed.Conclusion: Sending educational materials to patients with ADRD and caregivers may encourage them to talk with their doctors about stopping or reducing medications. Studies are needed to learn whether such materials lead to reductions in prescribing of potential harmful medications.

Validation of an ICD-10-based algorithm to identify stillbirth in the Sentinel System.

PURPOSE: To develop and validate an International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify cases of stillbirth using electronic healthcare data. METHODS: We conducted a retrospective study using claims data from three Data Partners (healthcare systems and insurers) in the Sentinel Distributed Database. Algorithms were developed using ICD-10-CM diagnosis codes to identify potential stillbirths among females aged 12-55 years between July 2016 and June 2018. A random sample of medical charts (N = 169) was identified for chart abstraction and adjudication. Two physician adjudicators reviewed potential cases to determine whether a stillbirth event was definite/probable, the date of the event, and the gestational age at delivery. Positive predictive values (PPVs) were calculated for the algorithms. Among confirmed cases, agreement between the claims data and medical charts was determined for the outcome date and gestational age at stillbirth. RESULTS: Of the 110 potential cases identified, adjudicators determined that 54 were stillbirth events. Criteria for the algorithm with the highest PPV (82.5%; 95% CI, 70.9%-91.0%) included the presence of a diagnosis code indicating gestational age ≥20 weeks and occurrence of either >1 stillbirth-related code or no other pregnancy outcome code (i.e., livebirth, spontaneous abortion, induced abortion) recorded on the index date. We found ≥90% agreement within 7 days between the claims data and medical charts for both the outcome date and gestational age at stillbirth. CONCLUSIONS: Our results suggest that electronic healthcare data may be useful for signal detection of medical product exposures potentially associated with stillbirth.

Validation of an electronic algorithm for Hodgkin and non-Hodgkin lymphoma in ICD-10-CM.

PURPOSE: Lymphoma is a health outcome of interest for drug safety studies. Studies using administrative claims data require the accurate identification of lymphoma cases. We developed and validated an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify lymphoma in healthcare claims data. METHODS: We developed a three-component algorithm to identify patients aged ≥15 years who were newly diagnosed with Hodgkin (HL) or non-Hodgkin (NHL) lymphoma from January 2016 through July 2018 among members of four Data Partners within the FDA's Sentinel System. The algorithm identified potential cases as patients with ≥2 ICD-10-CM lymphoma diagnosis codes on different dates within 183 days; ≥1 procedure code for a diagnostic procedure (e.g., biopsy, flow cytometry) and ≥1 procedure code for a relevant imaging study within 90 days of the first lymphoma diagnosis code. Cases identified by the algorithm were adjudicated via chart review and a positive predictive value (PPV) was calculated. RESULTS: We identified 8723 potential lymphoma cases via the algorithm and randomly sampled 213 for validation. We retrieved 138 charts (65%) and adjudicated 134 (63%). The overall PPV was 77% (95% confidence interval: 69%-84%). Most cases also had subtype information available, with 88% of cases identified as NHL and 11% as HL. CONCLUSIONS: Seventy-seven percent of lymphoma cases identified by an algorithm based on ICD-10-CM diagnosis and procedure codes and applied to claims data were true cases. This novel algorithm represents an efficient, cost-effective way to target an important health outcome of interest for large-scale drug safety and public health surveillance studies.

The Association of Nursing Home Characteristics and Quality with Adverse Events After a Hospitalization.

BACKGROUND/OBJECTIVES: We previously found high rates of adverse events (AEs) for long-stay nursing home residents who return to the facility after a hospitalization. Further evidence about the association of AEs with aspects of the facilities and their quality may support quality improvement efforts directed at reducing risk. DESIGN: Prospective cohort analysis. SETTING AND PARTICIPANTS: 32 nursing homes in the New England states. A total of 555 long-stay residents contributed 762 returns from hospitalizations. METHODS: We measured the association between AEs developing in the 45 days following discharge back to long-term care and characteristics of the nursing homes including bed size, ownership, 5-star quality ratings, registered nurse and nursing assistant hours, and the individual Centers for Medicare & Medicaid Services (CMS) quality indicators. We constructed Cox proportional hazards models controlling for individual resident characteristics that were previously found associated with AEs. RESULTS: We found no association of AEs with most nursing home characteristics, including 5-star quality ratings and the composite quality score. Associations with individual quality indicators were inconsistent and frequently not monotonic. Several individual quality indicators were associated with AEs; the highest tertile of percentage of residents with depression (4%-25%) had a hazard ratio (HR) of 1.65 [95% confidence interval (CI) 1.16, 2.35] and the highest tertile of the percentage taking antipsychotic medications (18%-35%) had an HR of 1.58 (CI 1.13, 2.21). The percentage of residents needing increased assistance with activities of daily living was statistically significant but not monotonic; the middle tertile (13% to <20%) had an HR of 1.69 (CI 1.16, 2.47). CONCLUSIONS AND IMPLICATIONS: AEs occurring during transitions between nursing homes and hospitals are not explained by the characteristics of the facilities or summary quality scores. Development of risk reduction approaches requires assessment of processes and quality beyond the current quality measures.

Characteristics of Long-Term Care Residents That Predict Adverse Events after Hospitalization.

BACKGROUND/OBJECTIVES: Adverse events (AEs) occur frequently in long-term care (LTC) residents transitioning from the hospital back to an LTC facility. Measuring the association between resident characteristics and AEs can inform AE risk reduction strategies. DESIGN: Prospective cohort analysis. SETTING: A total of 32 nursing homes from six New England states. PARTICIPANTS: A total of 555 LTC residents contributing 762 transitions from the hospital back to LTC. MEASUREMENTS: We measured the association between all AEs and preventable AEs developing in the 45 days following discharge back to LTC and demographic variables, hospital length of stay (LOS), Charlson Comorbidity Index (CCI) (0-1, 2-3, 4-5 and ≥6), dependency in activities of daily living (ADLs) using the Minimum Data Set Long Form Scale (in quintiles 0-12, 13-15, 16, 17-18, and ≥19), and number of regularly scheduled medications (0-9, 10-13, 14-17, and ≥18). To understand the independent association of each resident characteristic with AEs and preventable AEs, we constructed multiple Cox proportional hazards models. RESULTS: There were 283 discharges with one or more AEs and 212 with preventable AEs. Characteristics independently associated with higher risk of an AE included hospital LOS 9 or more days (hazard ratio [HR] = 1.49; 95% confidence interval [CI] = 1.02-2.17); CCI of 4 to 5 (HR = 1.74; 95% CI = 1.13-2.67) or 6 or higher (HR = 1.58; 95% CI = 1.01-2.46); 18 or more regularly scheduled medications (HR = 1.53; 95% CI = 1.07-2.18); and 19 and above on ADL dependency (HR = 1.78; 95% CI = 1.21-2.62). Results from models with preventable AEs were similar to those with all AEs. CONCLUSION: Increased LOS, higher comorbidity burden, greater dependency in ADLs, and polypharmacy were the resident characteristics most strongly associated with risk of AEs and preventable AEs. We recommend heightened vigilance in the care of LTC residents with these characteristics transitioning back to LTC. We also recommend research to assess strategies to reduce the risk of AEs.

Identifying monoclonal gammopathy of undetermined significance in electronic health data.

PURPOSE: Monoclonal gammopathy of undetermined significance (MGUS) is a prevalent yet largely asymptomatic precursor to multiple myeloma. Patients with MGUS must undergo regular surveillance and testing, with few known predictors of progression. We developed an algorithm to identify MGUS patients in electronic health data to facilitate large-scale, population-based studies of this premalignant condition. METHODS: We developed a four-step algorithm using electronic health record and health claims data from men and women aged 50 years or older receiving care from a large, multispecialty medical group between 2007 and 2015. The case definition required patients to have at least two MGUS ICD-9 diagnosis codes within 12 months, at least one serum and/or urine protein electrophoresis and one immunofixation test, and at least one in-office hematology/oncology visit. Medical charts for selected cases were abstracted then adjudicated independently by two physicians. We assessed algorithm validity by positive predictive value (PPV). RESULTS: We identified 833 people with at least two MGUS diagnosis codes; 429 (52%) met all four algorithm criteria. We randomly selected 252 charts for review, including 206 from patients meeting all four algorithm criteria. The PPV for the 206 algorithm-identified charts was 76% (95% CI, 70%-82%). Among the 49 cases deemed to be false positives (24%), 33 were judged to have multiple myeloma or another lymphoproliferative condition, such as lymphoma. CONCLUSIONS: We developed a simple algorithm that identified MGUS cases in electronic health data with reasonable accuracy. Inclusion of additional steps to eliminate cases with malignant disease may improve algorithm performance.

Adverse Events in Long-term Care Residents Transitioning From Hospital Back to Nursing Home.

IMPORTANCE: Transition from hospital to nursing home is a high-risk period for adverse events in long-term care (LTC) residents. Adverse events include harms from medical care, including failure to provide appropriate care. OBJECTIVE: To report the incidence, type, severity, and preventability of adverse events in LTC residents transitioning from hospital back to the same LTC facility. DESIGN, SETTING, AND PARTICIPANTS: Prospective cohort study of LTC residents discharged from hospital back to LTC from March 1, 2016, to December 31, 2017, and followed up for 45 days. In a random sample of 32 nursing homes located in 6 New England states, 555 LTC residents were selected, contributing 762 transitions from hospital back to the same LTC facility. MAIN OUTCOMES AND MEASURES: The main outcome was an adverse event within the 45-day period after transition from hospital back to nursing home. Trained nurse abstractors reviewed nursing home records for the period, and then 2 physicians independently reviewed each potential adverse event to determine whether harm occurred and to characterize the type, severity, and preventability of each event. When reviewers disagreed, they met to reach consensus. RESULTS: Of the 555 individual residents, 365 (65.6%) were female, and the mean (SD) age at the time of discharge was 82.2 (11.5) years. Five hundred twenty (93.7%) were non-Hispanic white, 21 (3.8%) were non-Hispanic black, 9 (1.6%) were Hispanic, and 5 (0.9%) were of other non-Hispanic race/ethnicity. In the cohort, there were 379 adverse events among 762 discharges. One hundred ninety-seven events (52.0%) related to resident care, with pressure ulcers, skin tears, and falls with injury representing the most common types of events in this category. Health care-acquired infections (108 [28.5%]) and adverse drug events (64 [16.9%]) were the next most common. One hundred ninety-eight (52.2%) adverse events were characterized as less serious. However, 145 (38.3%) events were deemed serious, 28 (7.4%) life-threatening, and 8 (2.1%) fatal. In terms of preventability, 267 (70.4%) adverse events were found to be preventable or ameliorable, with less serious events more often considered preventable or ameliorable (146 [73.7%]) compared with more severe events (121 [66.9%]). In addition, resident care-related adverse events such as fall with injury, skin tear, and pressure ulcer were more commonly deemed preventable (173 of 197 [87.8%]) compared with adverse drug events (39 of 64 [60.9%]) or health care-acquired infections (49 of 108 [45.4%]). CONCLUSIONS AND RELEVANCE: Adverse events developed in nearly 4 of 10 of discharges from hospital back to LTC. Most were preventable or ameliorable. Standardized reporting of events and better coordination and information transfer across settings are potential ways to prevent adverse events in LTC residents.