Designing a commercial bundle for cardiac procedures: The Percutaneous Coronary Intervention Episode Payment Model.

BACKGROUND: Cardiac interventions account for a significant share of overall healthcare spending and have been the focus of several large-scale interventions to develop effective bundled payments. To date, however, none have proven successful in commercially insured populations. In 2018, we worked with Hawaii Medical Service Association (HMSA), the Blue Cross Blue Shield of Hawaii, to design a novel commercial bundled payment for percutaneous coronary interventions, the Percutaneous Coronary Intervention Episode Payment Model (PCI EPM). METHODS: Descriptive analysis of HMSA's PCI EPM, including its inclusion criteria, contents of the bundle, target prices, shared savings model, and incentivized quality metrics. We also compare HMSA's PCI EPM to Medicare's Bundled Payment for Care Improvement programs and the cancelled Cardiac Care Model. RESULTS: HMSA's PCI EPM was designed through an iterative process with cardiologists and is the first commercial bundle to specifically target a cardiac procedure. PCI EPM incorporates site neutrality and incentivizes providers to shift care to the outpatient setting when medically permissible. Compared to existing non-commercial models, PCI EPM incorporate first-dollar shared savings and incentivized fewer quality metrics. CONCLUSIONS: Reviewing features of the Percutaneous Coronary Intervention Episode Payment Model in comparison to existing Medicare programs is intended to help guide health plan and health policymakers when designing programs and policies related to cardiac interventions. IMPLICATIONS: Bundled commercial payments for interventional cardiology procedures are promising and should continue to be further explored. LEVEL OF EVIDENCE: VI.

Designing a commercial medical bundle for cancer care: Hawaii Medical Service Association's Cancer Episode Model.

BACKGROUND: Oncology care is expensive and exhibits substantial variation in cost and quality across clinicians and patients. Unlike many conditions with established bundled payment programs, cancer care includes a mix of inpatient and outpatient care that precludes hospital-based designs. In 2018, we worked with Hawaii Medical Service Association (HMSA), the Blue Cross Blue Shield of Hawaii, to design a novel commercial bundle for cancer care, the Cancer Episode Model. METHODS: Descriptive analysis of HMSA's Cancer Episode Model, including its inclusion criteria, episode definitions, suite of enhanced services, shared savings model, and incentivized quality metrics. We also compare HMSA's Cancer Episode Model to Medicare's Oncology Care Model and three major commercial oncologic alternative payment models offered by Anthem, UnitedHealthcare, and Aetna. RESULTS: HMSA's Cancer Episode Model builds upon the successes and limitations of Medicare's Oncology Care Model and existing commercial alternative payment models. Compared to Medicare's Oncology Care Model, HMSA's Cancer Episode Model has stricter inclusion criteria, fewer incentivized quality metrics, a higher proportion of regional pricing, a different risk-adjustment model, and first-dollar shared savings. Compared to the majority of existing commercial models, HMSA's Cancer Episode Model includes total cost of care and a different risk-adjustment model. CONCLUSIONS: Reviewing features of the Cancer Episode Model in comparison to other programs is intended to provide guidance to health plans and health policymakers in the design of programs and policies aimed at improving cancer care value. LEVEL OF EVIDENCE: Level IV.

Crowdsourcing and the Accuracy of Online Information Regarding Weight Gain in Pregnancy: A Descriptive Study.

BACKGROUND: Excess weight gain affects nearly half of all pregnancies in the United States and is a strong risk factor for adverse maternal and fetal outcomes, including long-term obesity. The Internet is a prominent source of information during pregnancy; however, the accuracy of this online information is unknown. OBJECTIVE: To identify, characterize, and assess the accuracy of frequently accessed webpages containing information about weight gain during pregnancy. METHODS: A descriptive study was used to identify and search frequently used phrases related to weight gain during pregnancy on the Google search engine. The first 10 webpages of each query were characterized by type and then assessed for accuracy and completeness, as compared to Institute of Medicine guidelines, using crowdsourcing. RESULTS: A total of 114 queries were searched, yielding 305 unique webpages. Of these webpages, 181 (59.3%) included information regarding weight gain during pregnancy. Out of 181 webpages, 62 (34.3%) contained no specific recommendations, 48 (26.5%) contained accurate but incomplete recommendations, 41 (22.7%) contained complete and accurate recommendations, and 22 (12.2%) were inaccurate. Webpages were most commonly from for-profit websites (112/181, 61.9%), followed by government (19/181, 10.5%), medical organizations or associations (13/181, 7.2%), and news sites (12/181, 6.6%). The largest proportion of for-profit sites contained no specific recommendations (44/112, 39.3%). Among pages that provided inaccurate information (22/181, 12.2%), 68% (15/22) were from for-profit sites. CONCLUSIONS: For-profit websites dominate the online space with regard to weight gain during pregnancy and largely contain incomplete, inaccurate, or no specific recommendations. This represents a significant information gap regarding an important risk factor for obesity among mothers and infants. Our findings suggest that greater clinical and public health efforts to disseminate accurate information regarding healthy weight gain during pregnancy may help prevent significant morbidity and may support healthier pregnancies among at-risk women and children.

Exploring real-time patient decision-making for acute care: a pilot study.

INTRODUCTION: Research has described emergency department (ED) use patterns in detail. However, evidence is lacking on how, at the time a decision is made, patients decide if healthcare is required or where to seek care. METHODS: Using community-based participatory research methods, we conducted a mixed-methods descriptive pilot study. Due to the exploratory, hypothesis-generating nature of this research, we did not perform power calculations, and financial constraints only allowed for 20 participants. Hypothetical vignettes for the 10 most common low acuity primary care complaints (cough, sore throat, back pain, etc.) were texted to patients twice daily over six weeks, none designed to influence the patient's decision to seek care. We conducted focus groups to gain contextual information about participant decision-making. Descriptive statistics summarized responses to texts for each scenario. Qualitative analysis of open-ended text message responses and focus group discussions identified themes associated with decision-making for acute care needs. RESULTS: We received text survey responses from 18/20 recruited participants who responded to 72% (1092/1512) of the texted vignettes. In 48% of the vignettes, participants reported they would do nothing, for 34% of the vignettes participants reported they would seek care with a primary care provider, and 18% of responses reported they would seek ED care. Participants were not more likely to visit an ED during "off-hours." Our qualitative findings showed: 1) patients don't understand when care is needed; 2) patients don't understand where they should seek care. CONCLUSION: Participants were unclear when or where to seek care for common acute health problems, suggesting a need for patient education. Similar research is necessary in different populations and regarding the role of urgent care in acute care delivery.

Text messaging as a community-based survey tool: a pilot study.

BACKGROUND: It is not known whether using text messaging to administer real-time survey questions is feasible and acceptable among low-income, urban African American adults. METHODS: We used a mixed methods approach including paper surveys, surveys administered by text message, and a focus group. Survey questions that included multiple choice, Likert-like scales, and open ended questions were administered by paper and sent via text message daily during varied times of day for six weeks. RESULTS: In our study sample (n = 20), 90% of participants were female, and 100% were African American, with a median age of 30.7 years. Participants responded to 72% (1092/1512) of all multiple choice questions sent by text message and 76% (55/72) of the questions requiring responses on Likert-like scales. Content of responses on the paper and text message surveys did not differ. All participants reported in the focus group that they preferred text message surveys over other survey modalities they have used in the past (paper, phone, internet, in-person) due to ease and convenience. CONCLUSION: Text messaging is not only acceptable and feasible but is the preferred method of collecting real-time survey data in a low-income urban African-American community.